{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# ENSDF Nuclear Level Density Interpolation\n", "\n", "In the effort to use ML to predict cross section data, a very important feature that comes to mind are the nuclear levels. These are directly correlated to resonance location. How can we represent available data correctly and incorporate it into our EXFOR datasets? In this example, we go through a very simple approach where we load the cut-off ENSDF dataset and fit linear models to available nuclear level densities. It is not only the predictions that we save but also the models since we need to query them at the EXFOR datapoint energies." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T14:59:34.365488Z", "start_time": "2021-05-07T14:59:34.361986Z" } }, "outputs": [], "source": [ "# # Prototype\n", "import sys\n", "sys.path.append(\"..\")" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T14:59:58.066211Z", "start_time": "2021-05-07T14:59:57.462628Z" } }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "pd.set_option('display.max_columns', 500)\n", "pd.set_option('display.max_rows', 50)\n", "\n", "import logging\n", "import os\n", "\n", "import nucml.datasets as nuc_data\n", "import nucml.ensdf.plot as ensdf_plot\n", "import nucml.ensdf.data_utilities as ensdf_utils\n", "import nucml.model.building_utils as model_building\n", "import nucml.general_utilities as gen_utils" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T15:00:00.001309Z", "start_time": "2021-05-07T14:59:59.998288Z" } }, "outputs": [], "source": [ "figure_dir = \"../Figures/\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the modules imported, let us load the RIPL-cut ENSDF data." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:43:32.079315Z", "start_time": "2021-05-07T16:43:31.944815Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:root:Dropping Ground State...\n", "INFO:root:AME: Reading and loading Atomic Mass Evaluation files from: \n", " C:/Users/Pedro/Desktop/ML_Nuclear_Data/AME/CSV_Files\\AME_all_merged_no_NaN.csv\n", "INFO:root:Finished. Resulting dataset has shape (20825, 75)\n" ] } ], "source": [ "ensdf_cutoff_df = nuc_data.load_ensdf_ml(cutoff=True, log=True, append_ame=True, basic=-1, num=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Also, let us create a unique ID for each dataset:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:43:34.158346Z", "start_time": "2021-05-07T16:43:34.120847Z" } }, "outputs": [], "source": [ "ensdf_cutoff_df[\"ID\"] = ensdf_cutoff_df.Z.astype(str) + \"_\" + ensdf_cutoff_df.A.astype(str)\n", "unique_ids = ensdf_cutoff_df.ID.unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fitting a Simple Linear Model\n", "\n", "Having loaded the data we can fit a simple linear model to isotopic data using the `generate_level_density_csv()` utility. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:44:39.683739Z", "start_time": "2021-05-07T16:44:39.680237Z" } }, "outputs": [], "source": [ "import importlib" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:46:14.729055Z", "start_time": "2021-05-07T16:46:14.710553Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "importlib.reload(ensdf_utils)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:51:55.139062Z", "start_time": "2021-05-07T16:51:54.570563Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:root:Extracting samples from dataframe.\n", "INFO:root:ENSDF extracted DataFrame has shape: (36, 76)\n", "INFO:root:Generating level density for 233U\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "u233_nld = ensdf_utils.generate_level_density_csv(ensdf_cutoff_df, 92, 233, plot=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The function returns a DataFrame containing the Level Number, the Energy, and the Cumulative Number of Levels generated by the linear model." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:52:53.622014Z", "start_time": "2021-05-07T16:52:53.613012Z" } }, "outputs": [ { "data": { "text/html": [ "
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Level_NumberEnergyN
194882.00.0835392.0
194893.00.1123325.0
194904.00.1385979.0
194915.00.16313014.0
194926.00.18636520.0
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" ], "text/plain": [ " Level_Number Energy N\n", "19488 2.0 0.083539 2.0\n", "19489 3.0 0.112332 5.0\n", "19490 4.0 0.138597 9.0\n", "19491 5.0 0.163130 14.0\n", "19492 6.0 0.186365 20.0" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred_v1.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In our research efforts, we investigate ML models in data up to 20 MeV. This means we need nuclear level data up to that energy. The same function as above can be used but generate data up to those energies by giving the total number of levels to generate. " ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:54:52.534334Z", "start_time": "2021-05-07T16:54:51.696835Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:root:Extracting samples from dataframe.\n", "INFO:root:ENSDF extracted DataFrame has shape: (36, 76)\n", "INFO:root:Generating level density for 233U\n", "INFO:root:Extracting samples from dataframe.\n", "INFO:root:ENSDF extracted DataFrame has shape: (36, 76)\n", "INFO:root:Expanded Dataset has shape: (500, 75)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "u233_nld_exp = ensdf_utils.generate_level_density_csv(ensdf_cutoff_df, 92, 233, tot_num_levels=500, plot=True)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:54:59.931783Z", "start_time": "2021-05-07T16:54:59.927277Z" } }, "outputs": [ { "data": { "text/plain": [ "(500, 3)" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u233_nld_exp.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model is trained to predict the energy given a level number. We cannot just use the model to predict NLD although you could fit a linear model also to the generated NLD. That makes more sense but here I will opt for brute force as an example. The following function will keep increasing levels until the predicted energy reaches 20 MeV." ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T16:58:15.711994Z", "start_time": "2021-05-07T16:58:15.709493Z" } }, "outputs": [], "source": [ "# Since each iteration will generate a lot of output we will turn off the logger for now\n", "logger = logging.getLogger()\n", "logger.setLevel(logging.CRITICAL)" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T18:39:40.842194Z", "start_time": "2021-05-07T18:39:38.672693Z" } }, "outputs": [ { "data": { "image/png": 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zBR5vsVjk5+fn0Dtq1aqlESNGaPLkybmO8fX11VtvvaWBAwfq9OnTevrpp7V48WLdcccduvbaa1WpUiWdO3dO+/fv14oVK/TNN98oMzNTnTp10u23357r954/f/6Sny8rK0tnz57V4cOHtWnTJi1YsECnTp3KDtFXXXWVQz8bAABAaRc6I1R7Tu5xam5pC6V2hFMgB9u3b1fLli0LPL5Jkyb65ptvHH7PgAEDtHLlSm3fvj3XMU2bNtXcuXP1/PPPa+/evVq/fr3Wr1+f6/i+ffvqhRdekMViyXVMjx498q0tODhYUVFR6tq1a75jAQAAcAFXxDiHcAp4kGEYevnll9WrV688DzBq1qyZFi9erO+//17//e9/FRsbq1OnTikpKUmBgYGqWrWqbrzxRt1+++1OnaprGIb8/PxUqVIlNWjQQB06dNAdd9yR592mAAAAuFxh9paWdoZpmvyvUEQOHTqk8PBwRUdHO3Rn5N69e3XNNde4sTKg+OLvfwAA4A3olhZMXpmIA5EAAAAAoBCcDabh9cJLVTDND8t6AQAAAMAJAS8F6FzmOafmEkovRzgFAAAAAAc52y31NXyV9kKai6spGQinAAAAAFBAEfMiFP1HtFNz6ZbmjXAKAAAAAAXAoUfuRTgFAAAAgHxwRYz7EU4BAAAAIBeWKIuylOXUXIKpY7hKBgAAAAByYEQZTgXTplWaEkydQOcUAAAAAC4SMiVEiamJTs0llDqPcAoAAAAA/8MVMZ5DOAUAAABQ6ll3WXX/4vudmku31DUIpwAAAABKNa6IKR44EAkAAABAqeVsMF3QdwHB1MXonAIAAAAodcq+WFbpZrpTcwml7kHnFAAAAECpYkQZTgXT6uWrE0zdiM4pAAAAgFIhdEao9pzc49RcQqn7EU4BAAAAlHjO7i31kY8yJ2S6uBrkhGW9AAAAAEos6y6r08HUnGASTIsQnVPgfxo3bpz912XKlNGGDRsUHByc77ysrCx17NhRx48flyTdcMMNmj9/fvbnhw4dUnh4uCRp+PDhevzxx11bOAAAAHLEFTHehc4pkIOMjAytWbOmQGO3b9+eHUwBAABQPDgbTIe2Hkow9RA6pwWQkZGhefPm6YsvvtBff/2lK664Qp07d9bjjz+uoKAgT5cHN/nuu+9011135Ttu+fLlRVANAAAACiJkSogSUxOdmkso9Sw6pwUwatQovfrqq2rQoIHGjRunW265RVarVf/3f/+ntLQ0T5cHF2vUqJEkaePGjUpOTs5zbGZmplatWiVJqlKlittrAwAAQO6MKMOpYMoVMcUDndN8rFixQitWrNCDDz6oMWPGZD+vUaOG3njjDa1Zs0bdu3f3YIVwtU6dOumvv/7SuXPnFB0drT59+uQ6dsuWLTp58qTq16+vK6+8UidPnizCSgEAACBJw5YN08xtM52aSygtPuic5mPhwoUKCgrSk08+ecnzu+++W48++ijdshLI399fHTp0kGRb2puXFStWSJJ69Ojh9roAAABwOSPKcCqY+hq+BNNihnCah8zMTG3fvl033HCD/P39JUnnzp1TRkaGKlWqpBEjRuiGG27wcJVwh65du0qS1q9frzNnzuQ4JiMjI3tJb7du3YqsNgAAANgU5oqYtBfYnlfcEE7z8Ndffyk1NVU1a9bUsmXL1L17d11//fW6/vrr9fjjj+vvv//2dIkeY91lVd236sonykd136or6y6rp0tyqbCwMPn7+ys9PV3R0dE5jtm4caMSEhLUpEkTXX311UVcIQAAQOlV9sWyhQqmKJ4Ip3mwH4bz3//+V88995y6du2qd955RwMHDtT333+vyMjIfA/MKYmsu6wa8u0QxSXFyZSpuKQ4Dfl2SIkKqP7+/urYsaMkaeXKlTmOsZ/Sy5JeAACAomNEGUo30x2eF14vnGBazHEgUh7sJ/EePHhQ77//vjp16iRJuvXWW1WjRg29+OKLmjt3rp544gkPVnnBvJ/nac5Pc9z+nk2HNik1M/WSZynpKXr4m4f1wfYP3Pbeh1o8pIHNB7rt+/+ta9euWrlypTZs2KAzZ86ofPny2Z9d3FFlSS8AAID71ZhWQ0fOHHFqLqHUO9A5zYN9n2mtWrWyg6nd3XffLYvFoh9//NEDlXnWv4Npfs+9VadOnRQQEKDU1FStXbv2ks82bNigpKQkXXfddapVq5ZnCgQAACgljCjDqWAaXC6YYOpF6JzmoVq1apKkK6644rLPypYtq+Dg4FwPy/GEgc0HFklnse5bdRWXFHfZ8zpBdbT2gbVuf39RsS/tXbFihVauXKmePXtmf8aSXgAAAPez7rLq/sX3OzWXUOp96JzmoVKlSqpZs6YOHjyojIyMSz47c+aMTp06pZo1a3qoOs+ZHD5ZAb4BlzwL8A3Q5PDJHqrIfexLdtetW6eUlBRJtuXe0dHRMgyDJb0AAABuYkQZTgVTrojxXoTTfPTp00eJiYmaP3/+Jc8//PBDmaaZfeVIaRJ5baRm3T5LdYLqyJChOkF1NOv2WYq8NtLTpblcx44dFRAQoPPnz2cv7f3hhx905swZtWrVSldeeaVnCwQAACiBuCKmdGJZbz4GDx6smJgYvfrqq/rtt9/UvHlzbd++XUuWLNFNN92kO+64w9MlekTktZElMoz+m5+fnzp16qTly5fru+++U/fu3bVixQpJUvfu3T1cHQAAQMkSMiVEiamJTs2lW+r96Jzmw8/PT/PmzdOQIUO0efNmvfTSS9qxY4eGDRum999/Xz4+/E9Y0tmX7v7www9KTk5WTEyMLBZLqeyaAwAAuIsRZTgVTLkipuTw+s7psGHDFB0dLavVqtatW+c5dvfu3Zo9e7a2bNmixMREhYSEqGXLlho0aJBatmyZ67zAwEA9/fTTevrpp11dPryAfWlvSkqKXnvtNZ09e1Y333yzKleu7OnSAAAAvF7ojFDtObnHqbmE0pLFq8Op1WrNvmsyPytWrNCoUaMuOdjo+PHjWrlypVatWqWRI0dq8ODB7ioVXqxcuXIKCwvTsmXLtGjRIknO3226e/fu7O/Iy6233qrg4GCn3gEAAOAtnN1bGlwuWAljElxcDTzNa8PpokWLNGnSpAKN3blzp0aPHq2MjAy1bt1aTz/9tOrVq6c///xTb731ljZv3qzXX39dDRo0uOw+U0CyhdFly5bJNE35+vrqtttuc+p7YmJiFBMTk++4Zs2aEU4BAECJxRUxyInXhdO0tDRNmTJFVqu1wHPefvttpaWlqWHDhpozZ47KlSsnyXZVzOzZs/XAAw9o27Ztmjp1qjp06MA+UlymQ4cOCgwM1NmzZ3XLLbcoKCjI0yUBAAB4JUuURVnKcniej3yUOSHTDRWhuPCqcLp69Wq99tpriouLkySFhoZq9+7dec45cOCA1q9fL0kaOnRodjC18/X11TPPPKP+/fvrwIED2rFjR757V1Ey7du3L9fPypUrpx07duQ5f+7cuTk+r1mzZp7fDQAAUFo4u4x3Qd8FpeKmiNLOa8JpcnKyhg8fLkkKCAjQqFGj1KBBAw0cODDPeevWrZMkWSwWdejQIccxzZs3V+XKlfXPP/8oOjqacAoAAAC4UI1pNXTkzBGn5rKMt/TwqvWrFotFvXr10rJlyxQZWbDfOdm7d68kqVatWqpQoUKOYwzDUJMmTSQp304sAAAAgIIzogyngilXxJQ+XtM59ff316pVq1SzZk2H5h0+fFiS8p1XrVo1SdKhQ4ecKxAAAABAtoh5EYr+o2A3a/wbobR08ppw6uvr63AwlaSEBNsR07l1Te3snycnJzteHAAAAIBsXBEDZ3hNOHVWamqqJMnPzy/PcfaDkuzjAQAAADjO2WBKtxQlPpxaLBZJtn2lAAAAANwjZEqIElMTHZ7HFTGw86oDkZzh7+8vSTp//nye4wraYQUAAABwKSPKcCqYLui7gGCKbCW+c2rfS3r69Ok8x9n3moaEhLi9JgAAAKAkCJ0Rqj0n9zg1l2W8+LcS3zmtV6+eJOno0aN5jjt27JikC6f2AgAAAMidEWU4FUybVmlKMEWOSnzntGHDhpKkuLg4paSkKCAg4LIxpmlm34fatGnTIq0PAAAA8CbDlg3TzG0znZpLKEVeSnzntGPHjpKk9PR0rVu3LscxsbGxOnXqlCSpffv2RVYbAAAA4E0sURangmlwuWCCKfJV4sNp7dq11aJFC0nS9OnTdfbs2Us+T09P17Rp0yRJjRo1Urt27Yq8xoIwTf6fGaUPf98DAFB8GFGGspTl8DxzgsndpSiQEh9OJWns2LEyDEP79+/XgAEDtGnTJiUkJCg2NlaDBw/W1q1bZRiGRowYUSyvnLFYLMrIyPB0GUCRy8zMzL4OCgAAeEaNaTWcurvURz50S+GQEr/nVJKaN2+uqKgoTZw4Ubt379agQYMuGzNmzBh17tzZA9Xlr3z58kpOTlblypU9XQpQpM6cOZPjPnEAAFA0nAmlkjS09VC92+NdF1eDkq5UhFNJ6t+/v5o1a6Y5c+Zoy5YtSkhIUGBgoFq0aKFBgwYV2+W8ku16m0OHDikwMJB7WFFqZGZm6tSpU6pSpYqnSwEAoNSJmBeh6D+inZpLtxTO8upw2rZtW+3bt6/A40NDQ7P3l3oTf39/XXnllYqPj1dQUJDKly8vPz8/+fj4FMtlyICzTNNUZmamzpw5o1OnTikwMDD7rmIAAFA0nO2WNq3SVLsf2+3ialCaeHU4LU0qVqyocuXKKTk5WSdOnFBqaqqyshzfkA4UdxaLRQEBAapSpYoqVKjAb8AAAFBErLusun/x/U7NpVsKVyCcepFy5crpiiuu0BVXXOHpUgAAAFCCBLwUoHOZ5xyeV718dR0eedgNFaE0IpwCAAAApZizy3jplsLVCKcAAABAKRQ6I1R7Tu5xai7BFO5QKu45BQAAAHCBEWU4FUyHth5KMIXb0DkFAAAASolhy4Zp5raZTs0llMLdCKcAAABAKWCJsihLjt/2EF4vXGsGrnFDRcClCKcAAABACcYVMfAWhFMAAACghAqZEqLE1ESH5/lb/JXyfIrrCwLywIFIAAAAQAlkRBlOBdMFfRcQTOERdE4BAACAEiRiXoSi/4h2eJ6PfJQ5IdMNFQEFQzgFAAAASggjynBq3tDWQ/Vuj3ddXA3gGMIpAAAA4OU49AglAeEUAAAA8GIBLwXoXOY5h+c1rdJUux/b7YaKAOcQTgEAAAAv5ewyXrqlKI4IpwAAAICXCZ0Rqj0n9zg8jytiUJwRTgEAAAAv4my3dEHfBYq8NtLF1QCuQzgFAAAAvICzV8T4Gr5KeyHNDRUBrkU4BQAAAIo5S5RFWcpyeB5XxMCbEE4BAACAYoorYlCaEE4BAACAYqjGtBo6cuaIw/O4IgbeinAKAAAAFDNcEYPSyMfTBQAAAACwCZ0R6lQwDS4XTDCF16NzCgAAABQDXBGD0o5wCgAAAHjQsGXDNHPbTIfncUUMShrCKQAAAOAhZV8sq3Qz3eF5XBGDkohwCgAAABQxrogBLkc4BQAAAIoQV8QAOSOcAgAAAEWEK2KA3HGVDAAAAOBmw5YNcyqY+lv8CaYoNZzunJqmqX379mnnzp36888/dfz4caWkpMjHx0cBAQG68sorVa9ePTVv3lxXX321K2sGAAAAvAaHHgEF43A43bFjh7788kvFxMQoISGhQHMqV66srl27qnfv3mrWrJnDRQIAAADextkrYvwt/kp5PsUNFQHFW4HD6erVq/Xuu+/q119/lWTrnBbUyZMnZbVaZbVadeONN2rYsGFq06aN49UCAAAAXiDgpQCdyzzn8Dy6pSjN8g2nv/zyi6KiovTLL79kB9JKlSqpXbt2atKkiRo1aqQ6deqoYsWKKl++vHx8fHTu3DmdOHFChw8f1t69e7Vz505t3rxZp0+f1saNG7Vp0ya1atVKY8aMoZMKAACAEoVDjwDn5BpO09LSNG3aNC1YsECZmZmqWLGievbsqd69e+u6667L80srVKigChUqqH79+mrfvr0kKTMzU1u2bNGSJUu0cuVKbdu2Tffcc48GDx6s4cOHq0wZDg4GAACA94qYF6HoP6IdnscVMYBNronwzjvv1O+//65KlSppyJAhuueee+Tn5+f0iywWi9q1a6d27dpp7Nix+uyzz/TRRx/pvffeU0xMjL755hunvxsAAADwJEuURVnKcnge3VLgglyvkomPj9ejjz6q1atX64EHHihUMP23ihUrasiQIYqOjtbw4cMVFxfnsu8GAAAAior9ihhHg2lwuWCCKfAvuXZOly9frho1arj15QEBARo+fLjuvPNOt76nsJ544gl99913OX5mtVrVunXrIq4IAAAAnubsoUcL+i5Q5LWRbqgI8G65hlN3B9OLVatWrcje5Yx9+/apSZMmeuihhy77rH79+h6oCAAAAJ5i3WXV/Yvvd3geV8QAeeMUonycO3dO8fHxioyMVK9evTxdDgAAADyoxrQaOnLmiMPzuCIGyJ9bwun27du1du1apaam6tprr1X37t1lsVjc8Sq3++2335SVlaWGDRt6uhQAAAB4EFfEAO7lVDjNysrSp59+qs8//1wDBgzQ3Xffnf3Zm2++qVmzZl0y/v3339cHH3xQ7Jfv5uTXX3+VJDVo0ECSlJKSIj8/P/n45HqWFAAAAEqQYcuGaea2mQ7P44oYwDFOhdOxY8dqyZIlkmyn+tpt375d77//vgzDkGle+B2i/fv3a8iQIfrmm2+8LtTZw+ny5cv15JNP6sSJE/L399ett96qsWPHqlKlSh6uEAAAAO7i7KFHdEsBxzmcFLds2aJvvvlGpmmqYsWKuuqqq7I/s1qtkiTDMDRu3DitWrVKw4cPl2EY2r9/v77++muXFV5U9u3bJ0natWuXRo4cqenTp6tXr15aunSp7r33Xp0+fdrDFQIAAMDV7FfEOBpMuSIGcJ7DndOvvvpKklS9enV9+umnuvLKKyVJ6enpWrt2rQzD0I033qgBAwZIkoYPH64//vhDy5Yt03fffae+ffu6sHz369Onj2655RYNGTJEZcrY/ufq0qWL6tWrp1deeUVz5szRk08+6eEqAQAA4CohU0KUmJro8DwOPQIKx+HO6Y4dO2QYhh5++OHsYCrZlvSmpNiOxg4PD79kTteuXSVdWCLrTe6++24NGzYsO5ja3XfffSpTpow2bNjgocoAAADgStZdVhlRhsPB1N/iL3OCSTAFCsnhzumJEyckSY0bN77k+Y8//pj91zfddNMln1WtWlWSdOrUKYcLLK7Kli2rChUq6OzZs54uBQAAAIUUOiNUe07ucXge3VLAdRwOp+np6ZKkcuXKXfLcHk6vvPJK1atX75LPEhMTbS8r413Xqh49elRDhgxRaGiopkyZcslnp06dUkJCglq0aOGh6gAAAOAKZV8sq3Qz3eF57C0FXMvhZb32Luhff/2V/ezUqVPas2ePDMPQLbfcctmcnTt3StIlhyd5gyuvvFJnzpzRihUr9Mcff1zy2ZtvvilJXreHFgAAADb2Q48cDabVy1cnmAJu4HArs0WLFjp8+LA+//xz3XbbbSpTpow+/vhjZWVlyTAMRUREXDI+Pj5eCxYskGEYuv76611Vd5Hw8fHRhAkTNGzYMEVGRuq+++5TcHCwvv/+e23YsEG9e/fWrbfe6ukyAQAA4CBnr4hZ0HeBIq+NdENFABwOp3feeaeWLl2qLVu2qE+fPqpevbrWrVsnwzB01VVXqX379pJse1M/++wzLViwQElJSTIMQ3fddZfLfwB369Spk+bPn693331XH330kdLS0lSvXj298MILuvfeez1dHgAAABxg3WXV/Yvvd3hecLlgJYxJcENFAOwcDqft2rXTfffdp08++US///679u/fL9M0VaZMGU2cOFEWi0WSdOjQIc2YMUOGYUiSBgwYoFatWrm2eknDhg1TdHS0rFarWrdunefY3bt3a/bs2dqyZYsSExMVEhKili1batCgQWrZsmWu81q1aqXZs2e7unQAAAAUIQ49Aoo3p04oeuGFF3Tddddp8eLFOnnypOrXr6+HHnrokoBXv359SVKlSpWyl8W6mtVqVXR0dIHGrlixQqNGjVJGRkb2s+PHj2vlypVatWqVRo4cqcGDB7u8RgAAAHiWs91Sf4u/Up5PcUNFAHLi9PG5vXv3Vu/evXP9PCgoSFarVdddd518fX2dfU2uFi1apEmTJhVo7M6dOzV69GhlZGSodevWevrpp1WvXj39+eefeuutt7R582a9/vrratCggTp16uTyWgEAAOAZznZLw+uFa83ANW6oCEBu3Hq3izuW8aalpWnKlCmyWq0FnvP2228rLS1NDRs21Jw5c7KvwalUqZJmz56tBx54QNu2bdPUqVPVoUMH+fg4fIgxAAAAihlnrojxkY8yJ2S6qSIAefGqFLZ69Wr17NkzO5iGhobmO+fAgQNav369JGno0KGX3c/q6+urZ555Jnvsjh07XFw1AAAAipKzV8SE1wsnmAIelGvndOLEiS5/mWEYmjBhglNzk5OTNXz4cElSQECARo0apQYNGmjgwIF5zlu3bp0kyWKxqEOHDjmOad68uSpXrqx//vlH0dHR+R6sBAAAgOKpxrQaOnLmiMPzuLcU8Lxcw+lnn32WfdKuKzkbTiVbwOzZs6eeeuopVa9eXZs3b853zt69eyVJtWrVUoUKFXIcYxiGmjRpog0bNmj37t1O1wcAAADP4IoYwPvluefUNF37O0iFCbv+/v5atWqVatas6dC8w4cPS1K+86pVqybJdgUOAAAAvAdXxAAlQ67htKBXtBQVX19fh4OpJCUk2H4nLLeuqZ398+TkZMeLAwAAgEc4c+gR3VKgeMo1nNaoUaMo63Cb1NRUSZKfn1+e4+wHJdnHAwAAoPgatmyYZm6b6fA8uqVA8eXWq2SKA4vFIqlwS4oBAABQfIRMCVFiaqJDc3wNX6W9kOaeggC4RKHD6c6dO7Vp0yb99ddfSkpK0rPPPqsaNWooLi5OsbGx6tatm8qWLeuKWp3i7+8vSTp//nye4wraYQUAAIBnONstbVqlqXY/xqGXQHHndDg9cOCAxo0bp59//vmS58OGDZNkC61jxozRtGnTFBUVpbCwsMJV6iT7XtLTp0/nOc6+1zQkJMTtNQEAAMAxzl4Rs6DvAkVeG+mGigC4mo8zk2JjY9WvXz/9/PPPMk0z+4+LHTp0SKZp6vjx43rsscf0zTffuKRgR9WrV0+SdPTo0TzHHTt2TNKFU3sBAADgedZdVhlRhsPBtHr56jInmARTwIs4HE5TUlL0xBNP6OzZs/Lz89OIESP01VdfXTauZ8+e6tevnywWi7KysjRx4sTsa12KUsOGDSVJcXFxSklJyXGMaZrZ96E2bdq0yGoDAABA7kJnhDp1d+mCvgt0eGTR/3cngMJxOJx+9tlnOn78uPz9/fXJJ5/okUce0TXXXHPZuFq1aunFF1/UjBkzVKZMGZ0/f15Wq9UlRTuiY8eOkqT09HStW7cuxzGxsbE6deqUJKl9+/ZFVhsAAAAuZ++WOnp3qb/Fn24p4MUcDqfR0dEyDEP9+/fPMZT+W6dOndSvXz+ZpqkNGzY4VWRh1K5dWy1atJAkTZ8+XWfPnr3k8/T0dE2bNk2S1KhRI7Vr167IawQAAIBNxLwIp7ql4fXClfJ8zqvkAHgHh8PpgQMHJEkdOnQo8Bx79zI+Pt7R17nE2LFjZRiG9u/frwEDBmjTpk1KSEhQbGysBg8erK1bt8owDI0YMYIrZwAAADwkZEqIov+IdmiOvVu6ZuAaN1UFoKg4fFqvvfNYsWLFAs8JDg6WJGVmZjr6Opdo3ry5oqKiNHHiRO3evVuDBg26bMyYMWPUuXNnD1QHAABQull3WZ3qlnJFDFCyOBxOQ0JCdOLECR07dkzNmjUr0Jzffvste66n9O/fX82aNdOcOXO0ZcsWJSQkKDAwUC1atNCgQYNYzgsAAOABoTNCHd5basjQ/L7z2VsKlDAOh9NmzZopJiZGK1asUERERL7j09PTNW/ePBmGUeAwW1Bt27bVvn37Cjw+NDQ0e38pAAAAPCvgpQCdyzzn0By6pUDJ5fCe0549e8o0TS1fvlyrVq3Kc2xKSoqefvpp/f7775Kkrl27OlclAAAASoxhy4bJiDIcCqaGDC3ou4BgCpRgDndOu3fvrvnz5+unn37SiBEjdMcdd1yyJPbIkSNKSEjQpk2b9OWXX+qff/6RYRhq0qSJevbs6dLiAQAA4F1CpoQoMTXRoTnVy1fn3lKgFHA4nErSjBkzNGDAAB04cEBff/21vv766+xTbh977LFLxpqmqerVq2vGjBmchAsAAFBKDVs2TDO3zXR43tDWQ/Vuj3fdUBGA4sapcFqpUiV98cUXeuONN/TFF1/o3Lmcl2SUKVNGPXv21JgxY7JP7AUAAEDpUmNaDR05c8ShOf4Wf+4tBUoZp8KpJPn7+2vcuHF64okntHnzZu3du1cJCQnKyMhQcHCwGjZsqHbt2qlKlSqurBcAAABegitiADjC6XBqV6FCBUVERBTo5F4AAACUDlwRA8BRDofT//u//1OfPn0UERGhsmXLuqMmAAAAeDFnrojh0CMADl8ls27dOo0cOVI33XSTxo8fr23btrmjLgAAAHgZZ66IkWyHHhFMATjcOfX399e5c+d05swZffHFF/riiy9UvXp19e7dW7169VLt2rXdUScAAACKMa6IAVBYDndON27cqDfeeEOdOnWSxWKRaZo6fPiw3n33XXXp0kX33nuvFi5cqNOnT7ujXgAAABQj1l1WGVGGw8GUbimAf3O4c+rn56fu3bure/fuSkpK0ooVK7R06VJt375dpmkqNjZWsbGxmjx5sjp37qxevXqpQ4cO8vFxOAcDAACgGHPm0KPgcsFKGJPgpooAeLNCJcagoCDdc889WrBggb7//nuNHDlSDRs2lGmaSk1N1cqVKzV06FC1b99er7zyivbscewfXgAAACh+7N1SR4Pp0NZDCaYAcmWYpmm6+kv379+vb7/9VqtWrdIff/xhe5FhyDCMUh1QDx06pPDwcEVHR6tmzZqeLgcAAMBhEfMiFP1HtENz/C3+Snk+xU0VAfAmeWUit6y1bdCggYYMGaLHH39coaGhMgxDpmnKDTkYAAAARcC6yyqfKB+Hg2nTKk0JpgAKxOE9p3k5e/asVq9ereXLl2vTpk1KT0+XJJmmKX9/f912222ufB0AAACKgDPdUkOG5vedr8hrI91UFYCSptDhNC0tTWvXrtXSpUv1ww8/KDU1VZItkBqGodatW6tPnz7q0qWLAgMDC10wAAAAik6NaTV05MwRh+ZwRQwAZzgVTrOysrRhwwYtW7ZMa9as0dmzZyUpe9lunTp11KtXL/Xq1Us1atRwXbUAAAAoEtZdVt2/+H6H5w1tPVTv9njXDRUBKOkcDqdRUVFauXKlEhMTJV0IpBUrVlTXrl3Vu3dvtWzZ0qVFAgAAoOg4s4yXbimAwnI4nH766afZBxxZLBbdfPPN6t27tyIiIlS2bFl31AgAAIAiYN1l1aDFg5SpTIfmhdcL15qBa9xUFYDSwqllvQ0bNlSfPn10++23q0qVKq6uCQAAAEXMmW6pxbDo4z4fc+gRAJdwOJx+9dVXuuaaa9xRCwAAADzAmUOP6JYCcDWH7zklmAIAAJQMw5YNkxFlOBRMDRla0HcBwRSAyxXqKpmkpCQtWrRIGzdu1KFDh5ScnKx58+apYcOGio2N1aJFizRgwAA1adLEVfUCAADABUJnhGrPyT0OzeHQIwDu5HQ4/frrr/Xiiy/q3Llzki7ca5qZadtAv3//fn355Zf66quvNGjQID377LOuqRgAAABOs+6yasDiATJlOjSPZbwA3M2pcLpw4UJNmDDhkmtkkpOTLxnz999/S7LdiTp37lylp6fr+eefL2S5AAAAcJYz3dIyPmU0t/dcDj0C4HYO7zk9evSoXnrpJUlSo0aN9Omnn2rz5s2XjRs6dKhef/11ValSRaZpymq16qeffip8xQAAAHCIdZdVPlE+DgfT8HrhSh+fTjAFUCQcDqfz5s1TWlqaqlatqvnz56tFixYyDOPyL/bxUc+ePfXZZ58pJCREkvT5558XvmIAAAAUWMS8CN2/+H6HlvFaDAuHHgEocg6H0w0bNsgwDA0cOFBBQUH5jq9Zs6YeeOABmaapbdu2OVUkAAAAHFdjWg2H7y4NrxeujBcy6JYCKHIOh9PDh20ntDVv3rzAc66//npJ0okTJxx9HQAAABxkX8bryBUxdEsBeJrDByJlZGRIksqWLVvgORaLRZJtqS8AAADcx5lDj5pWaardj+12U0UAUDAOp8WqVatKsl0VU1D25bz2uQAAAHAtZw49sndLCaYAigOHw2mbNm1kmqYWLlxYoPF///235s6dK8Mw1LJlS4cLBAAAQN6cOfSoaZWm7C0FUKw4HE779+8vSfr555/1yiuvKCsrK9exu3bt0qBBg5SYmChJuvPOO52rEgAAADkKnRHq8KFHQ1sPpVsKoNhxeM9p8+bNdc899+izzz7TvHnz9P3336tt27bZn69atUorV67U5s2bFRsbK0kyDEM9evRQ69atXVY4AABAaWbdZdWgxYOUqcwCz6levroOjzzsxqoAwHkOh1NJGj9+vM6fP6+vv/5af/31lw4dOpR91+nMmTOzx5mmbWlJp06d9PLLL7ugXAAAAETMi3DqihhO4gVQnDkVTi0Wi6ZMmaKIiAjNnj1bsbGx2UH0Yg0bNtSDDz6ovn37FrpQAACA0s6ZbqnFsOjjPh+ztxRAsedUOLWLiIhQRESEkpOTtXfvXiUkJCgzM1NBQUFq1KgRp/MCAAC4CN1SACVdocKpXcWKFS/Zd1qSZWZm6r777tOuXbu0Z49jd4gBAAA4w5m7S4e2Hqp3e7zrpooAwPVcEk7zs337du3ebTsRbuDAgUXxSrd59913FRsbK4vF4ulSAABACefMMt4yPmU0t/dclvEC8DpFEk7XrFmjjz76SIZheHU4jY2N1cyZM1W2bFllZhb8XxIAAACOYhkvgNLG4XtOS6uzZ89q1KhR6tChg66//npPlwMAAEoo6y6rykSVcSiYlvEpowV9FxBMAXg1wmkBvfTSSzp79qxeeuklT5cCAABKIOsuq8q/XF73L77foWW84fXClT4+nWW8ALxekSzr9XYrV67U4sWLNWPGDFWpUsXT5QAAgBJm2LJhmrltZv4D/4VDjwCUJITTfPz999+aMGGC7rrrLkVERHi6HAAAUMI4s7eUQ48AlESE0zyYpqlnn31WFSpU0HPPPefpcgAAQAnjzBUxHHoEoKQinObho48+0qZNmzRjxgylpqYqNTVVkpSeni5JOnXqlHx9fVWhQgVPlgkAALwMV8QAwOUIp3mIiYmRaZoaNmxYjp+3a9dON9xwg+bPn1/ElQEAAG9k3WXVQ18/pLSsNIfm0S0FUBoQTvPw7LPPKjk5+bLnU6ZM0e+//67Zs2erYsWKHqgMAAB4G2cOPSpftrze6/ke3VIApQLhNA/NmjXL8XlQUJAMw9BNN91UxBUBAABv5Eww5SReAKVNruE0PDzcZS/JqfsIAABQ0jmzjJe9pQBKq1zD6eHDh2UYRlHWAgAAUGI40y1tWqWpdj+2200VAUDxlueyXtM0i6oOpw0bNkzR0dGyWq1q3bp1nmN3796t2bNna8uWLUpMTFRISIhatmypQYMGqWXLlgV+JwcgAQCA3Dh76BHLeAGUdrmG019//bUo63CK1WpVdHTBLq1esWKFRo0apYyMjOxnx48f18qVK7Vq1SqNHDlSgwcPdlepAACgFHCmW8pJvABg4+PpApy1aNEiTZo0qUBjd+7cqdGjRysjI0OtW7fWJ598oo0bN+rTTz9V27ZtlZWVpddff11r1651b9EAAKDEipgX4dShRwRTALDxunCalpamF198Uc8//3yBlx2//fbbSktLU8OGDTVnzhy1atVKlSpVUsuWLTV79my1bt1apmlq6tSpysrKcvNPAAAAShLrLqvKTSqn6D8KtppLkvwsflrQdwHLeAHgIl4VTlevXq2ePXvKarVKkkJDQ/Odc+DAAa1fv16SNHToUJUrV+6Sz319ffXMM89kj92xY4eLqwYAACVVxLwI3b/4fof2l4bXC9e5589xGi8A/IvXhNPk5GQNHz5ccXFxCggI0AsvvKBnn30233nr1q2TJFksFnXo0CHHMc2bN1flypUlqcB7WAEAQOlVmG4py3gBIGdeE04lW8Ds1auXli1bpsjIgv1u4969eyVJtWrVUoUKFXIcYxiGmjRpIsl2oi8AAEBuhi0bRrcUANwgz6tkihN/f3+tWrVKNWvWdGje4cOHJSnfedWqVZMkHTp0yLkCAQBAiRcxL8LhbumHvT4klAJAAXhNOPX19XU4mEpSQkKCJOXaNbWzf56cnOx4cQAAoERz5u5SrogBAMd4TTh1VmpqqiTJz88vz3H2g5Ls4wEAACTHu6WS7YoYTuIFAMfkuuf0559/1tGjR4uyFrewWCySbPtKAQAACoorYgCgaOUaTseMGaPOnTtnX8Nit3XrVm3dulXnzp1ze3Gu4O/vL0k6f/58nuMK2mEFAAAlnzOHHg1tPZRDjwCgEHJd1nvixAlJUsWKFS95PmDAAPn4+Gjx4sXZJ9wWZ/a9pKdPn85znH2vaUhIiNtrAgAAxZN1l1WPfPuIzqafLfAcDj0CANfItXOamZkp6cJptxczTdN9FblYvXr1JCnfJcrHjh2TdOHUXgAAULrYu6WOBFOuiAEA18m1c1q9enUdPHhQr7/+us6cOaOaNWuqTJkLw3/55Zd8u5E5adOmjXOVOqlhw4aSpLi4OKWkpCggIOCyMaZpZt+H2rRp0yKtDwAAeBbdUgAoHnINpz179tTbb7+tI0eO6IUXXrjkM9M0NX78eIdfZhiG9uzZ43iVhdCxY0e99NJLSk9P17p169SlS5fLxsTGxurUqVOSpPbt2xdpfQAAwHOsu6wa9NUgZZqZBZ7DFTEA4B65Luv9v//7P3Xt2lWmaV7yh92/nxf0j6JWu3ZttWjRQpI0ffp0nT176e+Kpqena9q0aZKkRo0aqV27dkVeIwAAKHrWXVYNWDzAoWA6tPVQgikAuEmundMyZcrorbfe0sGDB7V//36lpKTINE2NHTtWhmFo+PDhql69elHW6rSxY8eqf//+2r9/vwYMGKDRo0ercePGiouL05tvvqmtW7fKMAyNGDGCK2cAACjhnFnGW75seb3X8z2W8QKAG+UaTu3q16+v+vXrZ/967NixkqTw8HCvOK1Xkpo3b66oqChNnDhRu3fv1qBBgy4bY786BwAAlFzDlg3TzG0zHZoztPVQ7i0FgCKQbzj9N/uBRoGBgS4vxp369++vZs2aac6cOdqyZYsSEhIUGBioFi1aaNCgQSznBQCgBKNbCgDFn8PhdP78+e6owylt27bVvn37Cjw+NDQ0e38pAAAoHeiWAoB3cDic/tu6dev0ww8/6Pfff1diYqJ8fHwUFBSk+vXr66abblJYWJh8fHI9dwkAAMBtIuZFKPqPaIfmEEwBwDOcDqf79+/XqFGjcu1cbtq0SZ988omuvvpqvfHGG2rUqJHTRQIAADjCusuqh75+SGlZaQWewzJeAPAsp1qav/zyi/r166d9+/ZlXxFTpkwZValSRZUqVZLFYsl+vn//fvXr16/I7zcFAACl07Blw3T/4vsdCqZDWw/V6bGnCaYA4EEOd05TU1P1+OOPKyUlRZLUp08f3XfffWratKksFoskKSMjQ7t379Ynn3yib775RufPn9eIESO0ZMkSlStXzrU/AQAAgDj0CAC8ncPh9PPPP9fRo0dlGIZeeeUV9e7d+/IvLVNGzZs3V/PmzdWuXTuNHTtW8fHxWr58ufr06eOKugEAALI5eugRoRQAih+Hl/WuWbNGhmGoW7duOQbTf+vdu7e6desm0zT17bffOlMjAABAjqy7rCr/cnmHgml4vXCW8AJAMeRwON2/f78kqUePHgWe07NnT0nSH3/84ejrAAAAcmTfW+rIMt7weuFaM3CNG6sCADjL4XCanJwsSapatWqB51SpUkWSdPLkSUdfBwAAcBlnlvEu6LuAYAoAxZjD4TQoKEiSdPTo0QLPOXbsmCSpYsWKjr4OAADgEo4GU07iBQDv4HA4bdKkiSTp66+/LvAc+9jGjRs7+joAAABJju8vtXdL3+3xrpsrAwC4gsPhtEuXLjJNUzExMfr444/zHb9gwQJ9//33MgxDt956q1NFAgCA0s3R/aV0SwHA+zh8lUzv3r01Z84c/fnnn5oyZYo2bdqk/v37q3nz5goJCZEkJSQkaOfOnfrss8+0du1aSVLNmjV11113ubR4AABQsjl6d6khQ/P7zieUAoAXcjicli1bVm+99ZYeeughnTp1SmvXrs0OoD4+tkZsVlZW9njTNFWxYkXNmDFDvr6+rqkaAACUeI7uLbUYFn3c52OCKQB4KYeX9Uq2faeffvqp2rVrJ9M0s//IzMxUZmbmJc9uuOEGffnll2rUqJGrawcAACWUM6fxEkwBwLs53Dm1q1Onjj766CP9+uuvWrdunX7//XclJiYqKytLwcHBaty4sW655RZdc801rqwXAACUUNZdVj254kn9c+4fh+YNbT2UQ48AoARwOpzaNWnSJPsEXwAAAGc42imVbN3S93q+R7cUAEqIQodTAACAwnAmmNItBYCSh3AKAAA8wtGTeCW6pQBQkhFOAQBAkXO0W2rI0KOtH6VbCgAlGOEUAAAUKUeDaWX/ynq729t0SwGghCOcAgCAIuNIMGUJLwCULoRTAADgVs5cEcOBRwBQ+hBOAQCA23ASLwCgoHwcnXDixAl31AEAAEoYR4Np+bLltaDvAoIpAJRSDofTZ555Rrfddpu+/vprN5QDAAC8nXWXVVWmVnEomA5tPVSnx55mfykAlGIOL+vdt2+fEhMTlZaW5o56AACAFxu2bJje2/aeTJkFGs8VMQAAO4fD6dmztouyGzVq5PJiAACA9+KKGABAYTi8rLd+/fqSpL1797q8GAAA4J0cvSJmQd8FOjn6JMEUAJDN4XA6YsQIGYaht956Sxs3bnRHTQAAwEs4sr/UkMHeUgBArhxe1nvllVfqySef1Ntvv62HHnpItWvXVvPmzVWtWjUFBgbKMIw85//f//2f08UCAIDiw5H9pSzhBQDkx+Fw2qdPn+y/Nk1T8fHxio+PL/B8wikAAN7PkWW83FsKACgIh8OpaZp5/jov+XVVAQBA8WbdZdWTK57UP+f+KdB4gikAoKAcDqfz5s1zRx0AAKCYc2QZL1fEAAAc5XA4veGGG9xRBwAAKKYc7ZayvxQA4AyHwykAACg9HOmWSizjBQA4r9DhNDMzU7t27dJff/2l5ORkde/eXSEhIUpMTNS5c+dUrVo1V9QJAACKkKPdUpbxAgAKy+lweu7cOc2cOVOffvqpzpw5k/28VatWCgkJ0ZYtW/Tkk08qIiJCY8eOVfXq1V1SMAAAcC9Hu6Us4wUAuIJT4fTEiRN66KGHtH///ktO6734NN7Dhw/LNE2tWbNGW7du1UcffaRrrrmm8BUDAAC3oFsKAPAkH0cnmKapJ554Qr///rtM09RNN92kMWPGXDauSZMmql+/vkzTVGJioh577DGlpKS4pOiitn//fg0fPlw333yzWrZsqYEDB2rjxo2eLgsAAJcZtmyYBiwe4NChR/P7zieYAgBcxuFwumLFCv30008yDEOTJk3SnDlz9MADD1w2rl27dlq+fLkGDx4sSTp69Kg+//zzQhdc1A4cOKB+/frpp59+0v33368RI0YoOTlZDz74oFauXOnp8gAAKBTrLquqTK2imdtmFviKmKGth+rk6JMs4wUAuJTD4fTbb7+VJHXp0kV33313vuNHjRqlDh06ZC/x9Tavvfaa0tLSNG/ePA0dOlQDBgyQ1WpV1apVNXXqVE+XBwCA0+iWAgCKE4fD6S+//CLDMNSjR48Cz7nzzjsl2ZbHehPTNFW2bFl17dpVV199dfbzwMBAXX/99Tp8+LASExM9VyAAAE6gWwoAKI4cPhDJHsYcuSLGPvbs2bOOvs6jDMPQ9OnTL3uenp6uffv2qWLFiqpQoYIHKgMAwHGOHngkcRIvAKDoOBxOy5cvr8TERCUnJxd4ztGjRyVJFStWdPR1xUpiYqL279+v9957T3/++afGjx8vi8Xi6bIAAMiXo9fDcBIvAKCoORxO69evrx07dmjDhg266aabCjRn8eLFknTJ0lhv9Oijj+qnn36SJEVERKhPnz4erggAgPxZd1m5txQAUOw5vOc0PDxcpmnqk08+0R9//JHv+NmzZ+u///2vDMNQp06dnKmx2HjggQc0Y8YMDRo0SGvXrlW/fv2UlJTk6bIAAMiVdZdVg74axN5SAECx53A4ve+++1S1alWdP39eAwYM0FdffaW///47+3PDMJSWlqYff/xRjzzyiF5//XVJUnBwsO655x7XVe4BXbt2VUREhJ577jmNGzdO+/fv1/z58z1dFgAAl7EfenT/4vuVaWbmO56TeAEAnubwsl4/Pz+98847GjRokE6ePKnnnntOki2UStKDDz6o5ORkZWba/kVomqbKlCmjN954Q4GBgS4s3bPuuOMORUVF6ZdffvF0KQAAZHP00COW8AIAiguHO6eSdN1112nhwoVq0qSJTNPM/kOSTp06pYyMjOxntWrV0rx589SuXTuXFl4UDh06pNtuu00TJky47DP7ycPlypUr6rIAAMiRI/eWsoQXAFDcONw5tWvYsKG+/vpr/fjjj1q7dq327t2rhIQEZWRkKDg4WA0bNtQtt9yiW2+9VT4+TmVgj6tWrZrS0tK0dOlS/d///Z9q1qyZ/dl7770nSbr11ls9VR4AANkcOfTIYlj0cZ+PCaUAgGLF6XBqd9NNNxX41F5vY7FYNHHiRA0bNkz33nuvIiMjVb58ecXExGj9+vXq2rWrevTo4ekyAQClnCOHHgX4BmjW7bMIpgCAYqfQ4bSk69Spk+bPn693331Xs2bNUnp6uurVq6fnn39ekZGR2XttAQAoauwvBQCUJIUOp7t379aGDRu0b98+JSUlqWzZsgoODlZoaKhuueUW1alTxxV15mrYsGGKjo6W1WpV69at86119uzZ2rJlixITExUSEqKWLVtq0KBBatmyZa7zWrVqpdmzZ7u6dAAAnEIoBQCURE6H0507d2rSpEm5nlb71VdfZd9tOmHCBF155ZVOF5kbq9Wq6OjoAo1dsWKFRo0apYyMjOxnx48f18qVK7Vq1SqNHDlSgwcPdnmNAAC4knWXVUO+HaKU9JR8xxoy9GjrR7keBgDgFZw6qWjlypW677779Msvv1xyWq/FYpHFYsn+dVZWlmJiYtSnTx/t37/fpYUvWrRIkyZNKtDYnTt3avTo0crIyFDr1q31ySefaOPGjfr000/Vtm1bZWVl6fXXX9fatWtdWiMAAK5k31takGBqMSzcWwoA8CoOd06PHj2qMWPGKCMjQ4ZhqE+fPurTp4+aNm2q8uXLS5KSkpK0c+dOLVq0SKtWrdKpU6c0ZMgQLVu2TP7+/oUqOC0tTVOmTJHVai3wnLfffltpaWlq2LCh5syZk339S6VKlTR79mw98MAD2rZtm6ZOnaoOHTp47enCAICSydFlvBx6BADwRg6nsLlz5+r8+fMqU6aM3n33Xb3yyiu64YYbsoOpJAUFBal9+/aaPn26XnnlFRmGoaNHj2revHmFKnb16tXq2bNndjANDQ3Nd86BAwe0fv16SdLQoUMvu5fU19dXzzzzTPbYHTt2FKpGAABcyb6M15H9pQRTAIA3cjic/ve//5VhGLr33nsVFhaW7/g+ffqod+/eMk1TK1eudKpISUpOTtbw4cMVFxengIAAvfDCC3r22Wfznbdu3TpJtmthOnTokOOY5s2bq3LlypJU4D2sAAC4myPLeCv7V9aCvgt0cvRJgikAwCs5HE6PHTsmSbr11lsLPKdnz56SpLi4OEdfdwmLxaJevXpp2bJliows2L949+7dK0mqVauWKlSokOMYwzDUpEkTSbYTfQEA8BTrLqvqvlVXRpShAYsHKNPMzHO8xbAQSgEAJYLDe079/PyUmpoqi8VS4DkBAQG2l5Vx/uYaf39/rVq1SjVr1nRo3uHDhyUp33nVqlWTJB06dMi5AgEAKKR/n8RrysxzPHtLAQAlicOd0+uvv16SsvdxFkRsbKwk6ZprrnH0ddl8fX0dDqaSlJCQIEm5dk3t7J8nJyc7XhwAAIXkyBJeib2lAICSx+Fw+vDDD0uyHYxUkCWwR48e1QcffCDDMDRo0CDHKyyk1NRUSbaOb17sByXZxwMAUBSsu6yqMrWK7l98f75LeCWW8QIASi6Hw2mbNm307LPP6ty5cxowYIDmzp2rM2fOXDYuPT1d3333nfr166eEhAQNGTJEnTt3dknRjrAvPzYMo8jfDQBAXhw9iTfAN0Af9/mYUAoAKJFy3QTavHnzPCcahqGUlBS9+uqreu2111S3bl1VqlRJku2e0/j4eKWmpso0Tfn7+2vbtm26//77tWDBAtf+BPmw36t6/vz5PMcVtMMKAIAr2Jfx5tctNWTIlKk6QXU0OXwywRQAUGLlGk4LurzVNE1lZmbqwIEDOnDgQI5jzp8/r+3bt3uke2nfS3r69Ok8x9n3moaEhLi9JgBA6WbvmBbkJF46pQCA0iLXcNqmTZuirMNt6tWrpy1btujo0aN5jrNfkWM/tRcAAEdMnSq1aSNdfAV4TIy0das0erTt19ZdVo2LHqe4pPyvVuMkXgBAaZNrOJ0/f35R1uE2DRs2lGS7YzUlJSX7WpuLmaaZfR9q06ZNi7Q+AIB3s4fSNm2kfv2khQulrCzbnxcvtv3ZusuqJ1c8WeC9pZX9K+vtbm8TTAEApYrDByJ5m44dO0qyHdC0bt26HMfExsbq1KlTkqT27dsXWW0AAO9nD6WSNGuW1KWLFBEhffaZLZgeqVLwQ484iRcAUJqV+HBau3ZttWjRQpI0ffp0nT179pLP09PTNW3aNElSo0aN1K5duyKvEQDgfaZOtS3bDQuzhdBevaR77pHS022fd37Kqgd/rqv7F99foLtLOYkXAFDa5bqstyD27dun+Pj4ywJfXnr37l2YVzpl7Nix6t+/v/bv368BAwZo9OjRaty4seLi4vTmm29q69atMgxDI0aM4MoZAECB2Dumn30mrV4t2c/dK1tW6j7Gqq8zh0hJ+YdSSZzECwCAnAynGzZsUFRUlP766y+H5hmG4ZFw2rx5c0VFRWnixInavXu3Bg0adNmYMWPGeOQeVgCA97j40KOwMOm996SuXaWMDNvn5cpJxnVWLfEZJPnkfRKvxKFHAABczOFw+ssvv+jRRx9VRkaGTNN0R01u0b9/fzVr1kxz5szRli1blJCQoMDAQLVo0UKDBg1iOS8AIF/2bumnn0p790pjxlwIpi1aSN1GWzXt9yHKyso/mHLoEQAAl3I4nL7//vtKT0+XYRi67bbbFB4ersqVK6ts2bLuqC9Pbdu21b59+wo8PjQ0NHt/KQAABXVxx/S996Ru3Wyh1MfHtoy3zcNWbfQfp5/25X9FDEt4AQDImcPhdPv27TIMQz179tRrr73mjpoAAChW7B3T6dOlF16Q7AuHfH2lkXOteuvgEGXlc+gRS3gBAMibw+H09P9OfLjzzjtdXgwAAMXFv/eXjh0rRUZKhmELp3Vutyq+4Ti9XIBuqcWwEEwBAMiHw+G0atWqOnLkiMqVK+eOegAAKBYu3l+6bp304ou256Yp3TzUqp9qDpFZwCtiCKYAAOTP4XtOb7nlFknS1q1bXV4MAACeYr+31O7666WbbpJuu80WTH19JUsLqwLH1dWGqgW7u7ROUB2CKQAABeRwOB08eLACAgI0e/ZsxcfHu6MmAACKnL1TOmeO9MgjUrVq0pIlUpUq/xtwnVVl+gzRWd84KZ8rsQN8A7Sg7wL9+dSfBFMAAArI4WW9tWrV0uuvv64RI0bo7rvv1sCBA3XjjTeqatWqslgs+c6vXr26U4UCAOAu9v2lU6dKDz0kWSy2k3hvuUX69Vep6T1W7Wk0SCrAFTGcxgsAgHMcDqeS7UqW6667Tlu2bNE777yjd955p0DzDMPQnj17nHklAABuY++adu9u+3Vmpi2g7tolPfae7TRepecdTNlbCgBA4TgcTk+cOKF77rlHR48elWEYMu3n6QMA4IXsXdNPP5W6dLF1TH19pbQmVgX2LdhpvHRLAQAoPIfD6fvvv68jR45Ikvz8/HTDDTfoyiuvVNmyZV1eHAAA7mbvmt52m5SVZXuWFWpVmTuGKMHk7lIAAIqKw+F07dq1MgxD11xzjebMmaPg4GA3lAUAgPvZu6affCLdNtIqPTVOCopXuukjKe9lvNxdCgCAazm1rFeSHn30UYIpAMCr2bum9e6wSrcPkcr+r1NqsL8UAICi5vBVMhUrVpQkXXHFFS4vBgAAd/r3XaZHqliVOrSutta6/0IwzQd3lwIA4B4Oh9MWLVpIknbv3u3yYgAAcCd7pzQmRvp4h1WDvhii05b87y2VuLsUAAB3czicDho0SJL04YcfZi/xBQCguPl3l9Su2b1WhS+tqweW3K9Mn7y7pRbDIkMG3VIAAIqAw+G0VatWeuqpp3Ts2DHdddddslqtOnjwoNLS0txRHwAATrm4SypJX30ldX3GqrUVh8ismH+3NMA3QB/3+VhZE7LolgIAUAQcPhDpySeflCSFhITo77//1ksvvZT9mcVikcViyXWuYRiKjY11vEoAABwUFiYtXCj17SvVqiXt2iXbaby++e8tDTbq6J3bubcUAICi5HA4/e6772QYF3672TTN7L/OyMhQRkZGrnMvngcAgLvYr4hp3FhKqm1VYudxUt94SWae8ziFFwAAz3E4nLZp08YddQAA4DL2Jb1XRlhl9hxSoJN46wTV0eRwuqUAAHiKw+F0/vz57qgDAACn2TulYWG2Xx+pYlXKkHHa7VuwvaV0SwEA8DyHwykAAMWNvVO6cKEtmD7w5RBl5NMtNWSodlBtuqUAABQThFMAgNezH37Ur5+U9NA4ZQTkHUzrBNXRn0/9WTTFAQCAAnE4nB45cqRQL6xevXqh5gMAcLGpU22HHlmPjdPJxwp26NHk8MlFUxwAACgwh8Np586dnT511zAM7dmzx6m5AADkJKm2VS//MsR2RUw+/3riihgAAIovp5b1Xnx9DAAAnvTxofzvLuXQIwAAij+Hw2lkZN7/Ys/KytLp06d19OhR7dy5U+np6apTp46eeeYZlSnDFlcAQP7+ffquJMXESFu3Sg8+KL34lVVz/xqnM5b/LePNtWNqqA6HHgEA4BUcTovjx48v8NiEhARNmDBBq1at0jfffKP//Oc/jr4OAFAKXXz6bqtW0jvvSC+9JFWrJj27wCrdnv/dpRx6BACAd/Fx55eHhITozTffVNOmTbVmzRotW7bMna8DAJQQnTpJY8dKXbtKwcHSuHFSRoZUr54UfOe4fIOp0gMUeRWHHgEA4E3cGk4lyWKx6P7775dpmlq0aJG7XwcA8CJTp9qW69qlpEijRknVq0sjR0oWi2Sa0s2PWnXVq3X1fXsfJSou1+8zZKhOUB0912yWguJZxgsAgDcpkk2g9evXlyT9+uuvRfE6AICXsC/ffecdKTZWmjFDOn1auvpq6ZlnpI8+kro8Y9XXmUOkZJbxAgBQkhVJOD1x4oQk6fz580XxOgCAlwgLkyZNku65x/brsmWlN9+UrrtO6t/ftud0UOzYfIMpd5cCAOD93L6sNzMzUx9//LEkqXr16u5+HQDAC9iX86am2rqm5cvbnrdvL10RbtWd6+vqn+E+um9HNf2V/Feu32Nfxss1MQAAeD+HO6c7d+7Md4xpmjp37pwOHz6szz//XDt37pRhGOrUqZMzNQIAShj7ct4uXaTdu6WAAMnfX/rxtFXrvx6iVNPWKT125liu38EyXgAAShaHw2m/fv1kGLleKJerChUq6OGHH3Z4HgCg5AkLk557Tnr6aduhR2XKSF9/Ld2zeZyOp16+hNeQIVNm9q9ZxgsAQMnj1LJe0zQd+qN27dr64IMPVLlyZVfXDwDwEhefzLtvn22vqZ+flNnUKmNEXYX/4KPjqTmfxGvKVJ2gOizjBQCgBHO4czp8+PCCfXGZMqpQoYIaN26sli1bysfH7dtbAQDFmH0p7wcf2K6LSUuTzje0ytJniJIMTuIFAKC0c1s4BQDgYmFhttN3u3SRMjNt95cG3/WcEk1O4gUAAEV0lQwAoHSbOtXWOd1yzqr0x8ZJQfEql1ZdiebhXOcYMlQ7qLYmh09mCS8AAKUA4bQA/vzzT/3nP//Rxo0blZycrCuuuELh4eF68sknVaFCBU+XBwDFXps20h3jrEqJGCIF2zqlqeVyD6Ys4wUAoPTJNZweOXLELS/0trtO//77b/Xv31/p6em67777VLNmTf3888+yWq3avHmzFi5cKH9/f0+XCQDFWliYZOkyTlnKaQmvIXESLwAApV6u4bRz585OXRmTF8MwtGfPHpd+p7tNnTpVycnJ+vzzz3XddddJku655x41adJEL7/8sj777DM9+OCDHq4SAIof6y6rxkWPU3xSvKqXr60kM86WQy9jO4k3PimeZbwAAJRieS7rNU0zr49LhU2bNumaa67JDqZ2vXv31ssvv6ytW7cSTgHgX+552aqvM4coNcvWKT18JrdgyhJeAABgk2s4jYws3O9ap6Sk6Ntvv1VmZqYkW9D18/Mr1Hd6wsKFC5WWlnbZ81OnTkmyXZkDALhUjM84pabnv4S3nA9LeAEAgE2uyWr8+PFOf+mPP/6o8ePHXxJM27Rpo8mTve8/QGrUqJHj848++kiS1LZt26IsBwC8wonU+Fw+ubCE94pytRWWxRJeAABg49K235kzZzRlyhR9+eWXkmyhNDAwUKNGjdK9997ryld51LJly7Rw4ULVqFFDd955p6fLAQCPunhvae2g2mp45gH5GBZlmhmXjWUJLwAAyI3Lwun333+viRMn6sSJE9l7VTt06KAXX3xRV111late43FLly7Vs88+K39/f02fPt0rlyoDgKtYd1k15NshSvnfEt64pDjFKUpKDZSlrEWZRmr2WF+xhBcAAOTOp7BfkJCQoJEjR+qxxx7LDqbBwcF69dVXNWvWrBIVTGfNmqVRo0apXLly+uCDD9SsWTNPlwQAHjUuelx2ML1YsF8lZS6eLSXWkUxDIUYdlftulqqfZAkvAADIWaHC6bJly9SjRw8tX75cpmnKNE117dpVy5cvV69evVxVo8dlZWVp4sSJmjZtmipVqqR58+apdevWni4LADwuPinnvaWJWYcUcihSeutPPX4qS6de+FNLJkdq69YiLhAAAHgNp5b1Hj9+XBMmTNDatWsl2faWXnHFFZowYYIiIiJcWZ/HmaapcePGafHixapXr54++OAD1apVy9NlAYBHXLy/tFqFajJkkanL95YqqbYSE6X+/aVPP5X69JHCwmx/AAAA5MThcLpo0SK99tprOn36dPbe0r59+2rs2LGqUKGCywv0tDlz5mjx4sVq3LixPv74Y4WEhHi6JADwiH/vLz1y+ojtg6wyks9FATUtQMb3k/XZZ1K/flJMjO3PCxcSTgEAQO4KHE4PHTqk8ePHa9OmTZJsHcUaNWpo0qRJuummm9xWoCclJSXpnXfekSTdeuut+uGHHy4bU7VqVbVr166oSwOAIpfb/tIKvkE6k1BeZoV4Kam26hyYrA+nRcq+kCYszBZMt24lnAIAgNwVKJzOmzdPb775ps6fPy/TNOXj46PIyEiNHDlS/v7+7q7RY2JjY5WSYvsPMXtI/bd27doRTgGUeKZpKi4pLsfPTmeckt44KUkaMECat+TyMSzpBQAA+ckznB48eFDjxo1TbGxs9hLe+vXra/LkyWrRokWRFJifYcOGKTo6WlarNd9Dinbv3q3Zs2dry5YtSkxMVEhIiFq2bKlBgwapZcuWl43v2LGj9u3b567SAaBY+ve9pc/e/Ky+O/BdruN9TteWf6D02GPSnDm2ZbwEUQAA4Khcw+msWbM0Y8YMpaWlyTRNlSlTRg8//LCGDx8uX1/foqwxV1arVdHR0QUau2LFCo0aNUoZGRf2RR0/flwrV67UqlWrNHLkSA0ePNhdpQKAV8jp3tJhy4fJYlh0T+i9+uKXb5RhXFjaW8YMkN/GyVryrS2Qdu3K/lIAAOCcXMPpG2+8IcMwJEmGYcg0Tc2dO1dz5851+mWGYSg2Ntbp+RdbtGiRJk2aVKCxO3fu1OjRo5WRkaHWrVvr6aefVr169fTnn3/qrbfe0ubNm/X666+rQYMG6tSpk0vqAwBvlNu+0vJGVf3w5CfKqGyV5bZxyqwQr9oVa6vducl6ZHJkdhBlfykAAHBWvntO7ct5MzMzlZmZWaiX2cNuYaSlpWnKlCmyWq0FnvP2228rLS1NDRs21Jw5c1SuXDlJUqVKlTR79mw98MAD2rZtm6ZOnaoOHTrIx6dQ178CgNfK7d7SpMxjOntcmjgkUuPHRyqvf0yyvxQAADgj13Dapk2boqyjQFavXq3XXntNcXG2QzlCQ0O1e/fuPOccOHBA69evlyQNHTo0O5ja+fr66plnnlH//v114MAB7dixI9+9qwBQEiWnJivAN0Bn089e/mFSbY0ZI02YUPR1AQCA0iHXcDp//vyirCNfycnJGj58uCQpICBAo0aNUoMGDTRw4MA8561bt06SZLFY1KFDhxzHNG/eXJUrV9Y///yj6OhowimAUuHig48CdYUMS4bOZp5VGZ8yysi66N7S9AD1rjhZ770rde5MVxQAALiHV61ftVgs6tWrl5YtW6bIyMgCzdm7d68kqVatWqpQoUKOYwzDUJMmTSQp304sAJQE9oOP4pLiZMrUGR3X6YwEDaw9QdPD5qrMmTqSachIqqPnms3SV1GRWrjQdthRTIynqwcAACVRge45LQ78/f21atUq1axZ06F5hw8flqR851WrVk2SdOjQIecKBAAvkuPBR4apBb/M1fLRfyrjZKS6d5dGjRKHHQEAgCKRa+f0iSee0JEjR9xewNGjR/Xkk0/mO87X19fhYCpJCQkJkpRr19TO/nlycrLD7wAAb3Iu/ZzikuJy/CyrQrxOnpQGDpSWLbs8hIaFSaNHF0GRAACg1Mk1nK5evVrdunXTa6+9pqSkJJe/+NSpU3r11VfVrVs3rV692uXfb5eamipJ8vPzy3Oc/aAk+3gAKIk2H9qsFu+3yH1AUm117y4tX87yXQAAULRyDaezZs1ShQoVNGfOHIWHh+vVV1/VgQMHCv3CXbt2ady4cercubPmzp2rkJAQzZ49u9DfmxuLxSLJNdfYAIC3se6yqu5bdeUT5aOgKUG6cfaNSklP0Zibx8hXAZcOTgtQ7d8nq0MHsb8UAAAUuVz3nLZv315Lly7V1KlT9dVXX2nu3LmaO3euQkND1bFjR910001q0qSJAgMD83zBmTNntHPnTq1fv17R0dGKj7fdoWeapvr06aNx48apfPnyrv2pLuLv7y9JOn/+fJ7jCtphBQBvYT/0yL63NDk1WRbDohc6vKDBrQbL52QzTdk6TmbFeCmptgI2TtbZ3yN1w0j2lwIAgKKX54FIwcHBevnll9W/f39NmzZNW7Zs0S+//KLdu3fr3XfflWQ7SKhOnTqqUKGCypcvL4vFonPnzunEiRM6fPhw9oFEki2QGoahsLAwDRs2TM2aNXPvT6cLe0lPnz6d5zj7XtOQkBC31wQAReG56OcuO/Qo08zUS+te0uBWgzX5nkiFV41U165SVpbkW0FatPjSA5AIpgAAoKgU6LTe5s2ba968edq+fbsWLFigNWvWKD09XZJ05MgRHT16NMd5pmlm/7Wfn58iIiI0ePDg7GtbikK9evW0ZcuWXGu0O3bsmKQLp/YCgDfb9fcuxSfF5/jZxc9/+0363z/O9fjjhFEAAOA5Dl0l06pVK7Vq1UqnT5/Wf//7X23atEm7du1SfHy8zp07d8nYwMBA1alTR9ddd53atm2rDh065LsE2B0aNmwoSYqLi1NKSooCAgIuG2OaZvZ9qE2bNi3S+gDAlTKyMvTahtc0Ye0E+Rg+yjKzLhtTO6i2JOngQWnECMnXV3r2WWnmTLqlAADAc5y657RChQrq2bOnevbsmf3szJkzOnv2rAzDUGBgoEeCaE46duyol156Senp6Vq3bp26dOly2ZjY2FidOnVKkm2vLQB4C+suq8ZFj1N8Uryqla8mvzJ+Oph4UHc1vUvhdcM1cvXIS5b2lvMJ0OTwycrKkvr0kc6fl+67T5o0Serc2XYI0sKFBFQAAFD0cj2t11Hly5fXlVdeqapVqxabYCpJtWvXVosWtmsTpk+frrNnz17yeXp6uqZNmyZJatSokdq1a1fkNQKAM+wHHsUlxcmUqSNnjuhg4kE91uYxLbxroR5t86hm3T5LdYLqyJChquXqyHfFLFU/Ganp06WdOyU/P2nwYNv3XXwIEgAAQFFzWTgtzsaOHSvDMLR//34NGDBAmzZtUkJCgmJjYzV48GBt3bpVhmFoxIgRXDkDwGuMix532YFHkrT0t6XZ/yyLvDZSfz71p7ImZOnvMX9qyeRI3XmnNGqUVLastGzZpV3SsDBp9Oii+gkAAAAucGpZr7dp3ry5oqKiNHHiRO3evVuDBg26bMyYMWPUuXNnD1QHAI7LMrMUlxSX42e5HYQk2cJntWpSQoLtACT+sQcAAIqLUtE5laT+/fvriy++UM+ePVW1alX5+voqODhYYWFhmjt3rh544AFPlwgABRKXGKdb59+a6+f2A49y8uWX0p49Utu20oIFUkyMOyoEAABwnFd3Ttu2bat9+/YVeHxoaGj2/lIA8DamaWr2T7P19HdPy5Sph69/WJ/u/vSSpb0BvrYDj3ISEyMNHGj763nzpMOHOQAJAAAUH14dTgGgJLv4JN7qFaqrsn9l7Ty+U2F1wzSn1xzVDa6rsPph2WNqB9XW5PDJirw28pLvmTpVatNG2rxZCgyUbrrJFky3br1wABLhFAAAeBrhFACKIftJvPau6OHTh3X49GENvG6gPur9kXwM266MyGsjLwuj/9amja1D+uST0okT0i23XNoxJZgCAIDigHAKAMVQbifx/jfuv9nBtKDsV8R06SKVLy+98w5LeQEAQPFTag5EAgBvYZqmUyfx5uWWW6SMDOnMGWnoUIIpAAAofginAFCMHDl9RL0+65Xr53mdxJsXq1UyTal3b2nmTE7pBQAAxQ/hFACKAdM0Ne/neQp9N1SrD65WZLNIBfgGXDImr5N48xITY9tvKknjx9uW9PbrR0AFAADFS657To8cOeKWF1avXt0t3wsA3uTfJ/FeEXiFYo/F6uZaN+ujXh+pYeWGl4zJ7STegti6VerbV5o7V2rc2HZiL6f0AgCA4ibXcNq5c2cZhuHSlxmGoT179rj0OwHA2+R2Em/ktZH6uPfHsvhYJBXsJN782K+R+eknqW5dWzCNibEF09GjC/uTAAAAuE6ep/WapllUdQBAqZHbSbzr49dnB1NXsV8jU7Gi1LSpLZjar5EBAAAoTnINp5GRhfvd+pSUFH377bfKzMyUZAu6fn5+hfpOAPB27jiJNy9hYdJ770l33SVdeeWl95sCAAAUJ7mG0/Hjxzv9pT/++KPGjx9/STBt06aNJk92/CAPACgpDicf1pClQ3L93NmTePMTHS0ZhrRxo+1AJIIpAAAojlx6Wu+ZM2f0/PPP6+GHH9aRI0dkmqYCAgI0YcIEzZ8/X7Vru+c/vACgODNNU3Nj5yr03VDF/BGjAdcNcNlJvPn59Vfp/felcuVswZRrZAAAQHHlsnD6/fffq3v37vryyy9lmqZM01SHDh20bNky3Xvvva56DQB4lUPJh9Tjkx568JsH1fyq5to5dKfm9ZmnWbfPUp2gOjJkqE5QHc26fVahDz/KycMP2+43/eQT6cUXuUYGAAAUX3keiFQQCQkJeumll7R8+XJJtg5BcHCwxo4dq169cr9IHgBKmouvfqkVVEu3XX2bFu5eqIysDE3vOl2P3fCYfAzb7wm64iTe/Pzwg/Tjj7aA2qeP7VlYGNfIAACA4qlQndNly5apR48eWr58eXa3tGvXrlq+fDnBFECpYr8eJi4pTqZMxSfF68MdH6p6+era+ehOPd728exg6k5Tp9q6ollZ0qhRUs2atsOQpk69MCYsjGtkAABA8eNU5/T48eOaMGGC1q5dK8nWLb3iiis0YcIERUREuLI+APAKuV0Pk5KRoqsrXV1kddivjnnkEVt3dMwYacAAro4BAADFn8PhdNGiRXrttdd0+vTp7HtQ+/btq7Fjx6pChQouLxAAvEFu18D8lfRXkdZhX7YbEWG7OubDD7k6BgAAeIcCh9NDhw5p/Pjx2rRpkyRbt7RGjRqaNGmSbrrpJrcVCADFmWmamvPTnFw/d9f1MHm59lrbst6//+bqGAAA4D0KtAFq3rx5uv3227Vp0yaZpinDMHT//fdr6dKlBFMApVZ8Ury6Wrtq8LeD1aRKE/mX8b/kc3ddD5OfTz+1/fnee7k6BgAAeI88w+nBgwd177336pVXXtG5c+dkmqbq168vq9Wq559/Xv7+/nlNB4ASyTRNfbjjQzV7t5k2xG/Qu93f1S/DftEHd3xQJNfD5CUmRnruOdtfT57M1TEAAMB75Lqsd9asWZoxY4bS0tJkmqbKlCmjhx9+WMOHD5evr29R1ggAxUZ8Urz+79v/06oDqxRWN0yz75iteiH1JBXN9TD52bpV6t5dWrJEql1bqlePq2MAAIB3MEz7qUb/0qRJExmGkf1rHx8flSlTuGtRDcNQbGxsob7Dmx06dEjh4eGKjo5WzZo1PV0OgAK4+O7SEP8QnU07qzI+ZfTara/pkdaPFMn1MI66/XYpPl76+WdPVwIAAHCpvDJRvmnTnl0zMzOVmZlZqEIuDrsAUNzZ7y61XxFz6twp+Rg+mhIxRUPbDPVwdZebOtV2lcyvv0otW9qexcTYuqbcawoAAIq7XMNpmzZtirIOACh2not+7rK7S7PMLL216S09deNTnikqD/Y7Tv/5R7rvPlsw7dePO04BAIB3yDWczp8/vyjrAIBi5fd/fs/17tLcnntSerrtzzffLH3zjbRrl/Tuu9xxCgAAvEfhNpECQAmTmZWpNze9qfEx42XIkKnLt+V74u7SnBw7Jq1YIS1fLq1aJSUnS76+Uv360ldfcccpAADwLoRTAPifX47/ooe+eUhbj2xVr8a9FFE/Qs+uefaSpb2eurtUkrKypG3bbGF02TLbX0tS9eq25bs9etjC6QMP2ILpzJm2cEpABQAA3oBwCqDUS8tM0yvrXtHkdZMV7Besz+78TP1C+8kwDIX4h2Sf1ls7qLYmh08u0utiEhNtXdHly21d0uPHJcOQbrxReuklWyBt3tz27OI9pvZQevGvAQAAijPCKYBSbevhrXp4ycPadXyXIq+N1Ftd31KVgCrZnxf13aWmKe3ZY+uMLl8urV8vZWZKISFS1662MNqli1SlyuVzt269NIiGhXHHKQAA8B6EUwCl0rn0c5qwdoKmbZymauWr6dt7v1XPRj09UktKiq3raV+uGxdne37ddbYrYHr0kNq2lfK7ajqn62JY1gsAALwF4RRAqWDdZc1enls1sKpMmTp+9riGtByiqbdOVZBfUJHW8+efF7qj338vnT8vBQRIERHSc89J3bpJtWoVaUkAAAAeRTgFUOJZd1k15Nsh2Qcb/X32bxkyNPaWsXo5/GWXvGPqVNs9oxd3KWNibEtqR4+2XfWyYcOFQLpnj23M1VdLQ4bYuqMdOkh+fi4pBwAAwOv4eLoAAHC3cdHjLjlxV5JMmfpk1ycue0ebNrbDh2JibL+OiZHuukv65x/b8yuusAXXt9+WqlWT3nhD2rdP+v1327PbbiOYAgCA0o3OKYAS7dS5U4pLisvxs/ikeJe9x3740F13Sc2aST/+KGVk2Dqq1arZnvfoYVu2W6GCy14LAABQYhBOAZRYX+75Uo8tfyzXz2sH1XbZu1JTpU2bpORk6YcfpBo1pEcftQXS66+3XfUCAACA3LGsF0CJc+zMMd218C7dtegu1ahYQy93flkBvgGXjAnwDdDk8Mkued+qVbaTdZ97TvLxkR5/3BZWb75ZatGCYAoAAFAQhFMAJYZpmpr38zw1ndFUS39bqlfCX9HmwZs1tv1Yzbp9luoE1ZEhQ3WC6mjW7bMKfX9pfLxtuW6XLtKZM1LFitLKldL06bYlvhfvQQUAAEDeWNZbCD///LPuuecezZ8/X61bt/Z0OUCpFp8Ur0eWPqKV+1fq5lo3a/Yds9W4SuPszyOvjSx0GLVLTbUdaPTSS5JpSpP/14Bt1+7Cab32Pahbt3LPKAAAQEEQTp0UHx+v4cOHKysry9OlAKValpml97e9r9FrRss0TU3vOl2P3fCYfAz3LAxZtcq2bPe336Q+faQ335Tq1Ml5bFgYwRQAAKCgCKdOiImJ0ZgxY5SYmOjpUoBS7fd/ftfgbwfrh7gfFFE/Qh/c/oHqBtd1y7vi46Wnn5a+/FJq0EBasULq2tUtrwIAACiVCKcOGjlypJYuXaoGDRrolltu0dKlSz1dElAqWHdZNS56nOKT4lUrqJZurnWzvvr1K5WzlNPsO2brwesflOGGk4f+vYT3pZekUaOkcuVc/ioAAIBSjXDqoAMHDmjEiBF66KGH9P7773u6HKBUsO6yasi3Q5SSniLJtr80Pileraq10pJ7l6h6hepuea8jS3gBAABQOIRTBy1cuFBly5b1dBlAqTIuelx2ML3YiZQTbgmmLOEFAAAoelwl4yCCKVD04pPic3z+V9Jfhf7uqVMvXPeSmiq98orUqJH0zTe2Jby//EIwBQAAKAp0TgEUW8mpyXou+jmZMnP8vHZQ7UK/o00b232kzzwjzZ5tW8Jbtqw0b550772F/noAAAAUEJ1TAMXS0t+WKvTdUL279V11qd9F/mX8L/k8wDdAk8MnF+odpmnrllarJj37rHTihFSxorRyJcEUAACgqBFOARQrf5/5W/2/6K/bP71dwX7B2vjwRq0csFIf3PGB6gTVkSFDdYLqaNbtsxR5baRT78jMlL74QmrVSurWTUpIkG67zfbnJ5/kblIAAABPYFkvgGLBNE19FPuRRq0apbPpZ/VS2Et65uZnVNZi2+cdeW2k02HULi1NslqlKVNsy3cbNbIt5a1ZU4qMlMaPl2bOtIVTAioAAEDRonMKwOP2n9qviPkRenjJw7r2ymu189GdGtdhXHYwLayUFOk//7GdvPvQQ1JAgLRwobRnj1Svni2YLlwovfii7c/9+l04JAkAAABFg3AKwGPSM9M1Zf0UXTvzWm0/sl3v93xfMYNi1LhKY5d8f1KS7fTdunWlJ56QateWli+XduyQ7r5bslikrVttgdTeKQ0Ls/1661aXlAAAAIACYlkvAI/YdmSbBi8ZrJ///ll9r+mr/3T7j8vuLD1+XHr7bemdd6TkZNtVMM89J7Vvf/nY0aMvf8ayXgAAgKJXojqnw4YNU+PGjbVt27Z8x+7evVtPP/20brnlFjVr1kzt27fXk08+qR07dhT4fY8//rj27dun1q1bF6ZsoFQ5m3ZWI78bqbYfttXxs8e1uN9ifdnvS5cE0/h4W4e0bl1bx7RLF2n7dmnFipyDKQAAAIqPEtM5tVqtio6OLtDYFStWaNSoUcrIyMh+dvz4ca1cuVKrVq3SyJEjNXjwYHeVCpRaqw6s0iNLH9GfiX/qkVaPaErEFAX7BRf6e/ftk159VZo/3/brAQNsV8M0ds3qYAAAABSBEhFOFy1apEmTJhVo7M6dOzV69GhlZGSodevWevrpp1WvXj39+eefeuutt7R582a9/vrratCggTp16uTewoESzLrLqnHR4xSfFK8aFWuoTlAdbfhrgxpXbqwfHvhB7esUvpX500+2DukXX0h+ftLQodKoUba9pQAAAPAuXh1O09LSNGXKFFmt1gLPefvtt5WWlqaGDRtqzpw5KleunCSpUqVKmj17th544AFt27ZNU6dOVYcOHeTjU6JWPgNFwrrLqiHfDlFKeook6VDyIR1KPqTejXvr07s+lV8Zv0J9/7p1tlC6YoVUsaI0dqztftKqVV1RPQAAADzBa5PX6tWr1bNnz+xgGhoamu+cAwcOaP369ZKkoUOHZgdTO19fXz3zzDPZYx3ZfwrggnHR47KD6cV+OvaT08HUNC/sHe3QQdq2TXr5Zds+08mTCaYAAADezis7p8nJyRo+fLgkKSAgQKNGjVKDBg00cODAPOetW7dOkmSxWNShQ4ccxzRv3lyVK1fWP//8o+joaA47AhyUnpmuuKS4HD+LT4rPdd7UqVKbNpeekhsTI23eLF19ta1T+tNPUq1a0vTp0sMP2+4rBQAAQMngtZ1Ti8WiXr16admyZYqMjCzQnL1790qSatWqpQoVKuQ4xjAMNWnSRJLtRF8ABbfxr41qNatVrp/XDsp9M2ibNlK/frZAKkmrVkl33CHNmGF7fvasNGeOtH+/9PjjBFMAAICSxis7p/7+/lq1apVq1qzp0LzDhw9LUr7zqlWrJkk6dOiQcwUCpUzCuQSNjR6rWdtnqUbFGhpx4wi9v/39S5b2BvgGaHL45Fy/IyxMWrhQuvtuqXVrafVqKStLathQevNNqU8fyWIpip8GAAAAnuCV4dTX19fhYCpJCQkJkpRr19TO/nlycrLjxQGliGma+nz353pq5VM6kXJCT934lKI6RalCuQpqVb1V9mm9tYNqa3L4ZEVee/kqh6ws212ky5fb/vjnH+m772zLd2fNst1Vahge+OEAAABQpLwynDorNTVVkuTnl/eBLPaDkuzjAVzuYMJBDVs2TN8d+E6tqrXS8sjlalmtZfbnkddG5hhGJSkhwbZsd/ly2yFHJ07YAug119iW60ZGSl99JZUrRzAFAAAoLUpVOLX8b02gwX/tAk5Lz0zXtI3TFPXfKJXxKaPpXadrWJthsvjkvubWNKVduy50R3/8UcrMlCpVkrp2lbp3lwIDpf/7P2npUtsS33vvte01Xbjw0kOSAAAAUDKVqnDq7+8vSTp//nye4wraYQVKmw3xG/TI0ke0+8Ru9b2mr97u+rZqVsx5if3p01J09IVA+r8t32rZ0nYvaffu0g03XNhHOnXqpUHUvgd161bCKQAAQGlQqsKpfS/p6dOn8xxn32saEhLi9poAb5BwLkFj1ozRrB2zVDuotpbcs0S3N779kjGmKe3bdyGM/vCDlJ4uVawo3XabLYx27Sr977yxy4weffmzsDCCKQAAQGlRqsJpvXr1tGXLFh09ejTPcceOHZN04dReoLQyTVOf/fKZnvruKf2T8o9GthupiZ0mqnzZ8pKkc+ektWsvBNKDB23zQkOlp56yBdKbb5Z8fT32IwAAAMBLlKpw2rBhQ0lSXFycUlJSFJDDRYmmaWbfh9q0adMirQ8oTg6cOqChy4Zq9cHValO9jVZGrlSLai30xx/Sx/8Lo99/L50/bzvEKDxceuYZqVs3qU4dT1cPAAAAb+Pj6QKKUseOHSVJ6enpWrduXY5jYmNjderUKUlS+/bti6w2oLhIy0zTy+teVrOZzbTp0Ca9eet/9FK9jVrwegtdc41Uv740fLj022/SI4/Yrn355x9pyRLp0UcJpgAAAHBOqeqc1q5dWy1atNBPP/2k6dOn65ZbblFgYGD25+np6Zo2bZokqVGjRmrXrp2nSgU8Yn38ej2y9BHtObFHrfzu0hXb39L4l2vozBmpbFmpUydbAO3eXfrfQgQAAADAJUpVOJWksWPHqn///tq/f78GDBig0aNHq3HjxoqLi9Obb76prVu3yjAMjRgxgitnUGocP31KD3/2rJYe+VC+KbWlr7/V9t96qlYt6f77bWG0c2fbdS8AAACAO5S6cNq8eXNFRUVp4sSJ2r17twYNGnTZmDFjxqhz584eqA5wP+suq8ZFj1N8UrwqWWop+EQPHfT7QqbfKRmbRqlt+kTdMThQ3btLTZtK/B4NAAAAikKpC6eS1L9/fzVr1kxz5szRli1blJCQoMDAQLVo0UKDBg1iOS9KpKwsafISqyb9PETpSpEk/ZMZr38qzVT59Pp6ocEqDXn6egUFebhQAAAAlEolJpy2bdtW+/btK/D40NDQ7P2lQEmVkCCtWmU7WXfFCulE5DgpOOWycZWqZOiZAdcXfYEAAADA/5SYcApAMk1p584L945u3ChlZkqVKkldu0qfBMfnOO+vpL+KuFIAAADgUoRTwMudPi1FR18IpIcP2563bCmNHWs7zOjKRnEatWaE9KuZ43fUDqpdhBUDAAAAlyOcAl7GNKV9+y6E0R9+kNLTpYoVpdtus4XRrl2latWk1IxUvf7j65r83mRJ0t1N79ay35YpJePC0t4A3wBNDp/sqR8HAAAAkEQ4BYqVqVOlNm2ksLALz2JipB9/lFq0uBBI//jD9lloqPTUU7ZAevPNkq/vhXnf7f9Oj694XL+f+l19r+mrN7u8qdpBtS85rbd2UG1NDp+syGsji/TnBAAAAP6NcAoUI23aSP36SQsXSnXrSm+9Jb33nq1bmp4uBQRI4eHS6NFSt25SnTqXf0d8UrxGfDdCi/cuVsNKDbUycqW6NOiS/XnktZGEUQAAABQ7hFOgmDh/3hZAO3WSbr3VdpCRJFWvLt19t6072qGD5OeX8/zUjFS9sfENTfphkiRpcufJGtlupMqVKVc0PwAAAABQCIRTwIMOHrRd8bJihW35bkqKVK6crSN68KD02GPSO+/k/z2rDqzS8OXD9fup39WnSR+92eVN1QnOoa0KAAAAFFOEU6AInT8v/fe/FwLpb7/Znl99tfTQQ7aDjHx8pIEDpfHjpZkzpTvvvHQP6sXik+L19HdP68u9X6pBpQZaft9ydWvYreh+IAAAAMBFCKeAmx04cGl39Nw529LcTp1sndFu3aSGDW1jY2Iu7DkNC7P9cfGv7dIy07KX8JqmqZfCXtLIm0bKr0wua34BAACAYo5wCrjYuXPS2rUXAun+/bbnDRpIgwfbwminTpK//+Vzt269NIiGhdl+vXXrhWerD6zW4yse175/9ql3k956s8ubqhtctwh+MgAAAMB9CKeAC/z++4Uwunatbfmun58tUD7xhC2QNmiQ//eMHn35M3sH9a+kv/T0qqf1xZ4vdHXI1Vp23zJ1b9jd5T8LAAAA4AmEU8AJKSmXdkcPHLA9b9RIeuQRWxjt0CHn7qij0jLT9ObGN/XiDy8qy8zSi51e1DM3P8MSXgAAAJQohFOgAEzTdnjRypUXuqOpqbbw2bmzNGKELZDWr+/a9645uEbDlw/Xvn/2qVfjXnqzy5uqF1LPtS8BAAAAigHCKZCLs2dtBxTZu6N//GF73rixNHTohe5obveOFsah5EMauWqkFu5eqPoh9bX03qXq0aiH618EAAAAFBOEU+B/TFPat+9CGP3hB1t3NCBACg+XRo2yBdJ6bmxcpmWm6a1Nb+nF/76oTDNTUZ2iNPrm0SzhBQAAQIlHOEWpdvas9P33FwLpn3/anl9zzYVrXtq3l8qVc38t0QejNXzFcP168lfd0fgOvdXlLZbwAgAAoNQgnKJUMU1p715bEF250tYdTUuTAgNt3dFnn5W6dpXq1i26mg4nH9bIVSP1+e7PVS+4nr6991v1bNSz6AoAAAAAigHCKUq8M2ek6OgLgTQuzva8aVPp8cdt3dFbbima7ujF0jLT9PamtxX13yhlZGVoYseJGn3zaPn7uuCIXwAAAMDLEE5R4pimtGfPhaW669ZJ6elS+fJSRIT03HO27mjt2p6r8fs/vtfw5cO19+Re9WzUU293fVv1Q1x81C8AAADgRQinKBFOn77QHV2xQvrrL9vzZs2kp56ydUdvvlkqW7boa7Pusmpc9DjFJ8WreoXqqhVUS5sObVK94Hpacs8S3d749qIvCgAAAChmCKfwSqYp/fLLhTC6fr2UkSFVqGDrjo4fb+uO1qrl2Tqtu6wa8u0QpaSnSJIOnz6sw6cPq2+TvlrQdwFLeAEAAID/IZzCayQnS2vWXNg7euiQ7fl110kjR9q6o+3aeaY7mpvnop/LDqYX2350O8EUAAAAuAjhFMWWaUq7dl3ojm7YYOuOVqwo3XqrNHGirTtao4anK83Zzr93Kj4pPsfPcnsOAAAAlFaEUxQrSUnS6tW2zujKldLhw7bnzZtLo0Zd6I76+nq2zrwcOX1E478fr49iP5KPfJSlrMvG1A7y4GlMAAAAQDFEOIVHmab0888XuqM//ihlZkpBQbbuaLdutu5o9eqerjR/Z9PO6vUfX9fUH6cqPTNdT934lJpUaaIR3424ZGlvgG+AJodP9mClAAAAQPFDOEWRS0y0dUfte0ePHrU9b9FCevZZWyC98UapjJf83ZmZlamPf/5Yz3//vI6eOaq7mt6lKeFTdHWlqyVJgWUDs0/rrR1UW5PDJyvy2kgPVw0AAAAUL17yn//wZqYpxcZe6I5u3GjrjgYHS7fdZgujXbpI1ap5ulLHrT6wWqNWj9LOv3eqbY22WnT3It1c++ZLxkReG0kYBQAAAPJBOIVbJCRIq1bZwuh330nHjtmet2wpjRljC6Rt23pPd/Tfdh/frWdWP6MV+1eobnBdfXbnZ+oX2k+GYXi6NAAAAMAreWk0QHGTlSX99NOF7uimTbZnISG2rmi3brYu6VVXebrSwvn7zN96IeYFffjTh6pQtoJeu/U1Db9huPzK+Hm6NAAAAMCrEU7htFOnLnRHV66Ujh+3PW/dWho3zhZIb7hBslg8W6crpKSn6I2Nb+jVDa/qfMZ5PdbmMb3Q8QVVCaji6dIAAACAEoFwigLLypJ27LjQHd282fasUqUL3dEuXaSqVT1dqetkmVlasHOBxn0/ToeSD6l3k956NeJVNarcyNOlAQAAACUK4RR5Onny0r2jJ05IhmHrjj7/vC2QtmlTMrqj/xbzR4xGrhqpn479pNbVW2tBnwXqWLejp8sCAAAASiTCaSk2daotWIaFXXgWHS19/bVUpYotkG7ZYjttt0qVS/eOXnGFx8p2u19P/qrRq0fr29++Va2KtbSgzwLde+298jF8PF0aAAAAUGIRTkuxNm2kfv2kDz6Qzp6VPvpI+v57Wxg1DNt+0QkTbIG0VauS2R292ImzJzRx7US9v/19BfgG6JXwV/Rk2yfl7+vv6dIAAACAEo9wWoqFhUmffWbrhGZl2QJpeLj04IO2Z1VKyVk/59LP6e3Nb+vldS8rJT1Fj7R6RBM6TVDVwBK0eRYAAAAo5ginpVx4uHTffdKCBbYTdidN8nRFRSfLzNKnuz7Vc98/p/ikeN3e6Ha9GvGqrrniGk+XBgAAAJQ6bKIr5WJibNfAjB8vvfee7delwQ9xP+jGD2/U/V/dr8r+lRU9MFpL7l3y/+3de1TUdf7H8deIKCLeUBPylquICoogLbneScUUL+mWecjQjrXZ0f2t66rUmicvpWu6XdT2VyaVLurmL8Fbmoo3uqBYqXlZr4VKIhgiKHKT+f3BmQl0GAaEGcDn4xzPGef7+X558x3P58zLz+VLMAUAAAAchJFTG6Slpemdd97R/v37lZ6erg4dOuhPf/qTBg8e7OjS7svevYVrTj/7rHCK74ABxf9eE5359Yxm7Z6lmP/GqGWDlvp01Kd6ttuzbHYEAAAAOBjfyEtx69YtTZgwQdHR0Ro2bJgiIiLk5OSkqVOnKiYmxtHl3ZeEhOJBdMCAwr8nJDi2rspwLeua/mf7/8jnfR/tOr9L8wfM15mpZ/Sc33MEUwAAAKAKYOS0FFFRUTp9+rSWL1+uQYMGSZLGjBmjsWPHauHChRo8eLBcXV0dXGX5zJx573umEdSaIic/R8sOLdOCAwuUmZupSf6TNHfAXHm4eTi6NAAAAABFMGRUipiYGLVs2dIcTCWpTp06eu6555Senq4DBw44sDqUxGg06j/H/6NOKzppxq4Z+kPrP+jYS8f0wfAPCKYAAABAFUQ4tSIzM1MXLlyQn5/fPce6du0qSTp27Ji9y0Ipvrn0jf4Q+Qc98/kzali3oXY+u1NfhH0hn4d8HF0aAAAAgBIwrdeKq1evymg0ysPj3pG2Fi1aSJKSkpLsXRZKcD7tvCJiI/R/J/9Pnm6eWjVilcL9wuVUy8nRpQEAAAAoBeHUiszMTEmyuKbUxcVFknT79m271oR7pd1O04IDC7T80HI5Oznr9X6va/ofpsutjpujSwMAAABgI8KpFUajUZJkMBjuOWZ6z9Ix2EfunVy9n/C+5u2fp/TsdE3sPlHzg+fr4QYPO7o0AAAAAGVEOLXCNGJqaXQ0OztbkuTmxuicvRmNRm08tVGzds/S+evnNeh3g7Rk8BJ1a9HN0aUBAAAAKCfCqRWtWrWSVLj29G7JycmSZHE9KirPwcsHNX3ndH196Wv5NPfR9rDtCmkfwgg2AAAAUM0RTq1wc3NTu3bt9OOPP95zzLRLr6WdfFHxfrr+k17d86rWH1+vFvVb6IPQD/S8//OqXYt/wgAAAEBNwKNkShEaGqqff/5Ze/bsMb+Xm5urNWvWyN3dXX379nVgdTVfena6Zu6aqU4rOmnTfzdpdp/ZOjv1rF7s8SLBFAAAAKhB+HZfiokTJ2rz5s2aNm2aJkyYIE9PT0VHR+vkyZN66623zLv2omLl3cnT/x7+X83dP1dpt9M03m+83gh+Q60atnJ0aQAAAAAqAeG0FPXr11dUVJSWLl2q9evXKzc3V+3bt9eKFSs0cOBAR5dX4xiNRm06vUkzd83U2bSzGvDIAC0ZvEQBngGOLg0AAABAJar24fTll19WbGysoqKiFBgYaLXtiRMntGrVKh06dEjp6elq0qSJAgICFB4eroCAksNP8+bNtWjRooouHXc5/Mth/W3n37Q/cb86NeukLeO2aJjXMDY7AgAAAB4A1TqcRkVFKTY21qa227dv19/+9jfl5+eb30tJSdGOHTu0c+dOTZ8+XZMmTaqsUmHFxRsX9Wrsq4r6MUrNXZvr/aHva1LAJDk7OTu6NAAAAAB2Um3D6YYNGzR//nyb2h47dkwzZ85Ufn6+AgMD9de//lXt2rXTzz//rHfeeUcHDx7UkiVL1KFDB/Xv379yC3+ARf0Ypb/H/l0Xb1xUm0ZtNLvvbF24fkFvx78to9GoiF4RiugdoUYujRxdKgAAAAA7q3bhNDc3V4sWLVJUVJTN57z77rvKzc2Vl5eXIiMjVbduXUmSu7u7Vq1apQkTJujw4cNavHix+vbtq1q12MS4okX9GKUXt7yorLwsSVLijUS9sOUFSVJY1zC9EfyG2jZu68gSAQAAADhQtUphu3btUmhoqDmY+vj4lHrO+fPn9dVXX0mSJk+ebA6mJs7OzpoxY4a57ffff1/BVUOS/h77d3MwLcrDzUP/Hv1vgikAAADwgKs24TQjI0NTpkxRYmKiXF1dNWfOHM2aNavU8+Li4iRJTk5OJT6T1M/PT02bNpUkm9ewomwu3rho8f2rN6/auRIAAAAAVVG1CadSYcAcOXKktm3bprCwMJvOOXXqlCSpdevWatCggcU2BoNBnTp1klS4oy8qXptGbcr0PgAAAIAHS7VZc1qvXj3t3LlTrVq1KtN5SUlJklTqeZ6enpKky5cvl69AWPXG428UW3MqSa7Ornrj8TccWBUAAACAqqLajJw6OzuXOZhK0vXr1yWpxFFTE9PxjIyMsheHUoV1DdOHwz9U20ZtZZBBbRu11YfDP1RYV9tGwAEAAADUbNVm5LS8cnJyJEkuLi5W25k2SjK1R8UL6xpGGAUAAABgUbUZOS0vJycnSYXrSgEAAAAAVVOND6f16tWTJGVnZ1ttZ+sIKwAAAACg4tX4cGpaS5qZmWm1nWmtaZMmTSq9JgAAAABAcTU+nLZr106SdOXKFavtkpOTJf22ay8AAAAAwH5qfDj18vKSJCUmJiorK8tiG6PRaH4eapcuXexWGwAAAACgUI0Pp/369ZMk5eXlKS4uzmKbI0eOKC0tTZLUp08fu9UGAAAAAChU48NpmzZt5O/vL0l67733dOvWrWLH8/LytHTpUklSx44d1bNnT7vXCAAAAAAPuhofTiXplVdekcFg0Llz5zR+/HjFx8fr+vXrOnLkiCZNmqSEhAQZDAZNmzaNR84AAAAAgAPUdnQB9uDn56e5c+fq9ddf14kTJxQeHn5Pm4iICAUHBzugOgAAAADAAxFOJWns2LHy9fVVZGSkDh06pOvXr6t+/fry9/dXeHg403kBAAAAwIGqdTgNCgrS6dOnbW7v4+NjXl8KAAAAAKg6Hog1pwAAAACAqo1wCgAAAABwOMIpAAAAAMDhCKcAAAAAAIcjnAIAAAAAHI5wCgAAAABwOMIpAAAAAMDhCKcAAAAAAIer7egCHiR37tyRJCUnJzu4EgAAAACwP1MWMmWjogindpSamipJCgsLc3AlAAAAAOA4qampatu2bbH3DEaj0eigeh442dnZOn78uJo3by4nJydHlwMAAAAAdnXnzh2lpqbK19dXLi4uxY4RTgEAAAAADseGSAAAAAAAhyOcAgAAAAAcjnAKAAAAAHA4wikAi44eParOnTvr8OHDji4FQDWTlpamOXPmqF+/fvLz89OYMWO0c+dOR5cFoAbje0vNQDgFcI+LFy9qypQpKigocHQpAKqZW7duacKECYqOjtawYcMUEREhJycnTZ06VTExMY4uD0ANxPeWmoNwCqCYvXv36qmnnlJKSoqjSwFQDUVFRen06dP65z//qZkzZ2rcuHH697//rS5dumjhwoXKyspydIkAahC+t9QshFMAZtOnT9dLL72kZs2aKTQ01NHlAKiGYmJi1LJlSw0aNMj8Xp06dfTcc88pPT1dBw4ccGB1AGoSvrfUPIRTAGbnz5/XtGnTFB0drUceecTR5QCoZjIzM3XhwgX5+fndc6xr166SpGPHjtm7LAA1FN9bap7aji4AQNXx2WefqU6dOo4uA0A1dfXqVRmNRnl4eNxzrEWLFpKkpKQke5cFoIbie0vNQzgFarA333xT+fn5Vtv8+c9/VuPGjSWJDh7AfcnMzJQkubq63nPMxcVFknT79m271gSg5uJ7S81DOAVqsHXr1ik3N9dqm+eff94cTgHgfhiNRkmSwWC455jpPUvHAACQCKdAjfbjjz86ugQADxDTiKml0dHs7GxJkpubm11rAgBUH2yIBAAAKkSrVq0kFa49vVtycrIkWVyPCgCARDgFAAAVxM3NTe3atbM4a8O0S6+lnXwBAJAIpwAAoAKFhobq559/1p49e8zv5ebmas2aNXJ3d1ffvn0dWB0AoCpjzSkAAKgwEydO1ObNmzVt2jRNmDBBnp6eio6O1smTJ/XWW2+Zd+0FAOBuhFMAAFBh6tevr6ioKC1dulTr169Xbm6u2rdvrxUrVmjgwIGOLg8AUIUZjKZ93wHY3csvv6zY2FhFRUUpMDDQatsTJ05o1apVOnTokNLT09WkSRMFBAQoPDxcAQEBdqoYQHVHvwPAHuhrUB6sOQUcJCoqSrGxsTa13b59u55++mlt27ZNqampysvLU0pKinbs2KGwsDB99NFHlVwtgJqAfgeAPdDXoLwIp4ADbNiwQfPnz7ep7bFjxzRz5kzl5+crMDBQa9eu1bfffqt169YpKChIBQUFWrJkifbt21e5RQOo1uh3ANgDfQ3uB+EUsKPc3FzNmzdPs2fPlq0z6t99913l5ubKy8tLkZGR6tGjh9zd3RUQEKBVq1YpMDBQRqNRixcvVkFBQSX/BgCqG/odAPZAX4OKQDgF7GTXrl0KDQ1VVFSUJMnHx6fUc86fP6+vvvpKkjR58mTVrVu32HFnZ2fNmDHD3Pb777+v4KoBVGf0OwDsgb4GFYVwCthBRkaGpkyZosTERLm6umrOnDmaNWtWqefFxcVJkpycnEp8NqCfn5+aNm0qSTav7wBQ89HvALAH+hpUJMIpYCdOTk4aOXKktm3bprCwMJvOOXXqlCSpdevWatCggcU2BoNBnTp1klS42x0AmNDvALAH+hpUFJ5zCthBvXr1tHPnTrVq1apM5yUlJUlSqed5enpKki5fvly+AgHUOPQ7AOyBvgYViZFTwA6cnZ3L3GlL0vXr1yWpxP9RNDEdz8jIKHtxAGok+h0A9kBfg4pEOAWqsJycHEmSi4uL1XamTQRM7QGgvOh3ANgDfQ0sIZwCVZiTk5OkwjUXAGAP9DsA7IG+BpYQToEqrF69epKk7Oxsq+1s/d9HACgN/Q4Ae6CvgSWEU6AKM62zyMzMtNrOtA6jSZMmlV4TgJqNfgeAPdDXwBLCKVCFtWvXTpJ05coVq+2Sk5Ml/bajHQCUF/0OAHugr4ElhFOgCvPy8pIkJSYmKisry2Ibo9FoflZYly5d7FYbgJqJfgeAPdDXwBLCKVCF9evXT5KUl5enuLg4i22OHDmitLQ0SVKfPn3sVhuAmol+B4A90NfAEsIpUIW1adNG/v7+kqT33ntPt27dKnY8Ly9PS5culSR17NhRPXv2tHuNAGoW+h0A9kBfA0sIp0AV98orr8hgMOjcuXMaP3684uPjdf36dR05ckSTJk1SQkKCDAaDpk2bxnbsACoE/Q4Ae6Cvwd1qO7oAANb5+flp7ty5ev3113XixAmFh4ff0yYiIkLBwcEOqA5ATUS/A8Ae6GtwN8IpUA2MHTtWvr6+ioyM1KFDh3T9+nXVr19f/v7+Cg8PZ6oLgApHvwPAHuhrUJTBaDQaHV0EAAAAAODBxppTAAAAAIDDEU4BAAAAAA5HOAUAAAAAOBzhFAAAAADgcIRTAAAAAIDDEU4BAAAAAA5HOAUAAAAAOBzhFAAAAADgcIRTAAAAAIDDEU4BAAAAAA5HOAUAOFxERIS8vb3L9Sc4ONjR5T9wli5dKm9vb61Zs6bY+3d/NmvXri3TdZctW1bs/A8//LDCaj5z5sx9/5sZNWqUvL291aVLF129elWS9MUXX8jb21uvvvpqhdUKAA8qwikAALDZ4cOH9dFHH6l9+/YaN26c1bZffvllma69Y8eO+ynNqo4dO8rX11eSlJSUpO+//75M5589e1anTp2SJPXu3VstWrSQJA0dOlQBAQH6/PPPtXv37ootGgAeMLUdXQAAAEUtWLDAHCJs4ezsXInVoKi8vDy99tprKigo0IwZM1S7tvWvEQkJCUpLS5O7u3up1z5z5ozOnTtXUaVaNHr0aB0/flyStG3bNgUEBNh87qZNm8yvx4wZU+zYrFmzNHbsWM2dO1ePPfaY3NzcKqZgAHjAMHIKAKhS2rRpo86dO9v8p0OHDo4u+YHxySef6MKFC/L399eAAQNKbNe0aVNJ0p07d2weTdy+fbskqU6dOvdfaAlCQ0PN19++fbvu3Llj03kFBQXasmWLJKlJkyb3/O7du3dXcHCwUlJStHz58ootGgAeIIRTAABQqszMTK1cuVKSNGnSJKttO3furFatWkmyfWqvKZz26dPnPqq0rlGjRnr88cclSb/++qu+/fZbm847ePCgkpOTJUkjRoywGKBffPFFSVJUVJR5PSoAoGwIpwAAoFRr1qzRjRs31Lx5c/Xv37/U9iEhIZIKg92NGzestv3vf/+rn376SQaDQUOGDKmIcks0evRo8+utW7fadM7mzZvNr++e0mvi7+8vLy8v5ebmmkM8AKBsCKcAgBrHtCvrJ598IknauXOnXnjhBfXq1Uu+vr7q37+/Zs2apZMnT5Z6rStXrmjx4sUaMWKEevTooW7duunxxx/XrFmz9MMPP5R4nmnn2cDAQBmNRq1atUrBwcHy9fVVv379NHPmzGLtCwoKtGnTJoWHh+v3v/+9unbtqoEDB2rBggVKSUlRamqq+ffauHGjJCk3N1dBQUHmHWiNRqPV32XSpEny9vZWr169lJ+fX+rvbnLnzh2tX79ekjR8+PBS15pKMofMvLw8xcbGWm1rGjXt0aOHeaOh0pT3cym6mdGuXbuUk5Nj9edkZ2ebR399fHzk7e1dYtuRI0dKkqKjo5WVlWXT7wEA+A3hFABQYxUUFGj69OmaOnWqDhw4oGvXrikvL09XrlxRTEyMxowZo88++6zE8zds2KCQkBCtWrVKp0+f1s2bN5WTk6PLly8rJiZGzzzzjObMmaO8vDyrdSxdulSLFy9WUlKS8vLylJycLCcnJ/Px7OxsTZ48WTNnzlR8fLxu3Lih3NxcXbp0SWvWrNGwYcMs7i5bp04dDRs2TFLhDrTfffddiTVcu3ZN33zzjaTCqam2BEyTuLg481TVvn372nROt27d1LJlS0mlT+01hdOhQ4fadO37+Vxq1aplDpE3b97Uvn37rP6s2NhY3bp1S1LJo6Ym/fr1M193586dNv0uAIDfsFsvAKDGioyMVGpqqtq3b68JEybI29tbN27cUHR0tL744gsVFBRo/vz56tWrlzlImWzcuFGzZ8+WJHl6eiosLEzdu3eXs7Ozzp07p3Xr1un48eP6z3/+o9zcXC1atMhiDbdu3dLKlSvl5eWlKVOmqFmzZoqPjy8W8v7yl7+YQ5KPj4/Cw8P1yCOP6MqVK1q3bp3i4+M1ffp0i9cfPXq0oqKiJBVOPw0MDLTYbuvWreYNgEaNGmXzPZRkHvl0cXFRjx49bD4vJCREkZGR+vrrr3Xz5k2Lu9ieOHFCiYmJqlWrlgYPHqwLFy5YvWZFfC6jR482P0N169at5inIlph26a1bt66GDx9utbaOHTuqefPmSk1N1e7du8t8nwHgQUc4BQBUKRcvXlTDhg1tbt++ffsSd3hNTU1Vz5499cEHH6hu3brm9/v27auGDRtq/fr1ys3N1bZt28wb2kjS1atXNW/ePElSQECAVq5cWSxYde/eXU8++aReeeUVbdq0SdHR0Ro6dKjFUcWCggI1aNBAq1evNj9SpWiA3L17t/bu3StJGjBggJYtW2Z+PI6fn5+GDBmiBQsWaM2aNRZ/R19fX3Xs2FFnzpzRl19+qddee83i43VM6ya7dOlidWqqJfHx8ZKs32tLnnjiCUVGRiovL0979uzRiBEj7mljGjV99NFH1bx5c6vhtKI+l3bt2snf318//PCD9u/fX2Jw/vXXX/X1119LkgYNGmTTv8tOnTopNTVVBw8elNFolMFgKPUcAEAhpvUCAKqU2bNna9SoUTb/SUlJKfV6RYOpyTPPPGN+ffr06WLH1q5dq9u3b8tgMOgf//iHxeDi5OSkOXPmqFGjRpKk1atXl1hDSEhIic/6NJ3n6uqqhQsXWgyWERER+t3vflfi9U2b/KSnp+vAgQP3HD937pxOnDghqeyjpjdu3NDFixclSV5eXmU615apvTt27JBk25TeivxcTPcsJyenxCm4W7duNa/NLW1Kr4npHmVkZOinn36y6RwAQCHCKQCgxmrRokWJz0Ft3bq1+bVpTaGJaYptq1at1KZNmxKv7+bmZp7mevjw4RLXnnbv3t3i+xkZGeZ1osHBwWrSpInFdrVr17YajoquIS26s6yJaWqqs7NzqVNT75aYmGh+be1elMQ0ZTYuLu6e+3zs2DFdunRJtWvX1uDBg0u9VkV+LkOHDlW9evUklbxrr+m+Pfzww+rZs2ep9UnSI488Yn5d9N4BAErHtF4AQJWyevVqBQUFVci1TM/atKR+/frm10V3rs3Pz9eZM2ckSZcuXbJ5Cuzt27f166+/ysPD455jlt6TpLNnz5p/dteuXa1e38/Pr8RjTZs2Vd++fbVnzx7t3bu32DRVo9GoLVu2SCqczlzSCG5Jio5Ml2W6tcmQIUMUGRmpnJwc7d+/v9gIqWlK72OPPVZqXRX9ubi5uWnQoEHavHmz4uPjde3aNTVr1sx8/Pz58+bR5ieffNLm6bkNGjQwvy5tVB8AUBwjpwCAGss0MmZJ0bBR9BEsGRkZKigoKNfPK+l5npamn0qFaxpNGjdubPXapYW3kqapHjx4UFeuXJFUGLLKqugjUUr6Pazx8/PTww8/LOm3Kbwmpqm+TzzxRKnXqYzPxXTP7ty5Yw7KJqYRaIPBUOzZqKUpGk55nAwAlA0jpwAAFFF0FLVPnz4l7pJrSdu2bS2+X9KoW9HppqU9o7Q0/fv3l7u7u9LS0rR582ZzoDJNTW3cuLH5USdlUbT2WrXK93/aISEh+vjjjxUXF6fs7Gy5uLjoyJEjSkpKkrOzswYNGlTqNSrjc3nsscfUsmVLJSUladu2bRo/fryk4qPNQUFBVkfg71b0frEZEgCUDeEUAIAiio5g3rx5U507d660n1V0jWlaWprVtunp6VaPOzs7KzQ0VKtXr9bBgweVlpamBg0aaNeuXZKk0NDQMu20a1J0+nN2dnaZz5cKp/Z+/PHHysrK0oEDBzR48GDzKGqvXr3MmxdZUxmfi8Fg0KhRo7RixQr98MMPunTpklq3bq2EhAQlJSVJsn0jJJOi96jovQMAlI5pvQAAFFGnTh3zSNvx48d18+ZNq+03bNigqKgo7du3r9joni06depkfn3y5EmrbU3rH60xBamCggLt3btXCQkJyszMlFS+Kb2S9NBDD5lfp6amlusafn5+8vT0lCTzlOOyTOmVKu9zKbqe1FTTtm3bJBVO0bVlo6aiit6jovcOAFA6wikAAHfp3bu3pMJpt+vWrSux3ZUrV/T6669r3rx5mj9/vnnHXFu5u7ubd/Ldu3evOUjezWg0KiYmptTrderUyTyiuHv3bsXGxkoqfLyJr69vmWozKbr7rGk0sawMBoN51959+/bpu+++0y+//KI6depo4MCBNl+nMj6X1q1b69FHH5VUeM8KCgrM923o0KFycXGxuT6p+D2y9vgfAMC9CKcAANxl/PjxcnJykiQtW7ZMCQkJ97TJzc3VjBkzzKNypvWKZRUeHi6p8HE2r732mu7cuXNPm/fff9+mkVPpt01+vvnmG/OU3rI+27QoNzc3c8g6depUua8zZMgQSVJmZqYWLVokqXD34LJsslRZn4vpnh09elS7du0yj37+8Y9/tLk2E9M9cnd3L9NaVQAAa04BAFXMxYsXy/zIEk9Pz1J3uy2Ldu3aadq0aVqyZIlycnI0ceJEPfXUUwoODlb9+vV1/vx5ffrppzp79qwkqVu3bgoLCyvXzxo6dKiio6N14MABbd++Xb/88ovGjx+vtm3bKiUlRRs3bjSP5JlY22hn+PDhWrx4sbKzs5WdnS0nJyeNGDGiXLWZBAUF6cKFCzp37pyysrLk6upa5mt0795dHh4eSk5O1rFjxySp2GNlbFFZn0tISIjmzZunrKwsvfHGG5IKR5u7detWpvoKCgp0/PhxSYX3jA2RAKBsCKcAgCpl9uzZZT5n4cKFZXrchy1eeOEFGQwGvf3228rLy9PatWu1du3ae9oFBgZq+fLlcnZ2LvfPevvtt/XSSy8pISFBR48e1dGjR4sdb9asmZ588kmtXLlSkqxubNSkSRMNGDDAvLazV69e9732MSQkROvWrVNeXp4OHjyoAQMGlPkapqm9n376qSTJxcWlXNepjM/F1dVVTzzxhD7//HNdvXpVUtk3QpIK18KaNq4yjRQDAGzHtF4AAEowadIk7dixQxMnTpS3t7caNGig2rVrq1mzZurXr5+WLl2qNWvWFNt1tzzc3Ny0evVqvfnmmwoKClLjxo3l7OysNm3a6Pnnn9fWrVuLrV8sbeSy6CZD5d0IqaigoCB5eHhIKlyXWV5FA1u/fv3KNQIrVc7nUvQ/N5ydnTVy5Mgy12Ua4W7cuHG5gjcAPOgMxvt9sBoAAKh0H3/8sXmt5sa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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "u233_20mev = ensdf_utils.generate_level_density_csv(ensdf_cutoff_df, 92, 233, plot=True,\n", " get_upper=True, upper_energy_mev=20, it_limit=500)" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T18:39:40.849199Z", "start_time": "2021-05-07T18:39:40.844696Z" } }, "outputs": [ { "data": { "text/plain": [ "(3700, 3)" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u233_20mev.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Saving Predictions and Model\n", "\n", "We can now iterate through all elements in the `ensdf_cutoff_df` dataframe and use the same function to generate a CSV file and a `joblib` model that we can later used as needed. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T17:05:13.413736Z", "start_time": "2021-05-07T17:04:59.721735Z" } }, "outputs": [], "source": [ "# This list will allow us to obtain those isotopes for which we could not reach the target energy\n", "not_reached = []\n", "\n", "for i in unique_ids:\n", " Z, A = i.split(\"_\")\n", " df_str = ensdf_utils.generate_level_density_csv(ensdf_cutoff_df, int(Z), int(A), save=True, tot_num_levels=500, \n", " get_upper=True, upper_energy_mev=20, it_limit=500,\n", " saving_dir=\"Level_Density/\")\n", " if type(df_str) == str:\n", " not_reached.append(df_str)\n", "\n", "not_reached" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You will notice that the `not_reached` list is empty. I found that 500 iterations allowed enough loops for every element to reach 20 MeV. We can take a look at the directory and see that we succesfully generated various isotopic files with level density data along with the saved linear model." ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T17:06:24.612380Z", "start_time": "2021-05-07T17:06:24.605381Z" } }, "outputs": [ { "data": { "text/plain": [ "['100Mo_Level_Density.csv',\n", " '100Mo_linear_model.joblib',\n", " '100Ru_Level_Density.csv',\n", " '100Ru_linear_model.joblib',\n", " '101Ru_Level_Density.csv',\n", " '101Ru_linear_model.joblib',\n", " '102Pd_Level_Density.csv',\n", " '102Pd_linear_model.joblib',\n", " '102Ru_Level_Density.csv',\n", " '102Ru_linear_model.joblib']" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "os.listdir(\"Level_Density/\")[:10]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting Level Density at a Given Energy\n", "\n", "Having the resultant files and DataFrame means we can query level density at various energies to get the cumulative number of levels." ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T18:39:49.892517Z", "start_time": "2021-05-07T18:39:49.888014Z" } }, "outputs": [], "source": [ "u233_20mev.Energy = np.log10(u233_20mev.Energy)" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "ExecuteTime": { "end_time": "2021-05-07T18:40:08.568696Z", "start_time": "2021-05-07T18:40:08.561193Z" } }, "outputs": [ { "data": { "text/plain": [ "3.255272505103306" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.log10(ensdf_utils.get_level_density(1, u233_20mev))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Perfect!" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 4 }